Index (predict4all-core 1.2.0 API)

A B C D E F G H I K L M N O P Q R S T U V W _
All Classes All Packages

A

ABBREVIATIONS - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageUtils
AbstractLanguageModel - Class in org.predict4all.nlp.language
AbstractLanguageModel() - Constructor for class org.predict4all.nlp.language.AbstractLanguageModel
AbstractNGramDictionary<T extends AbstractNGramTrieNode<T>> - Class in org.predict4all.nlp.ngram.dictionary: Represent an ngram dictionary in an abstract way : dictionary can be static or dynamic.
Each type of dictionary can or can't support operation, such as dictionary saving, or updating probabilities.

The dictionary has a AbstractNGramDictionary.maxOrder that represents the max order gram that can be found in the dictionary.
AbstractNGramDictionary(T, int) - Constructor for class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Construct a dictionary with a given root node and a max possible order.
AbstractNGramTrieNode<T extends AbstractNGramTrieNode<?>> - Class in org.predict4all.nlp.ngram.trie: Represent a node in a trie structure to represent ngrams.
AbstractNGramTrieNode() - Constructor for class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode
AbstractPredictionToCompute - Class in org.predict4all.nlp.prediction.model
AbstractPredictionToCompute() - Constructor for class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
AbstractRecursiveMatcher - Class in org.predict4all.nlp.parser.matcher
AbstractRecursiveMatcher(boolean, Separator, String) - Constructor for class org.predict4all.nlp.parser.matcher.AbstractRecursiveMatcher
AbstractRecursiveMatcher(boolean, Separator, String, EquivalenceClass) - Constructor for class org.predict4all.nlp.parser.matcher.AbstractRecursiveMatcher
AbstractTokenTrainingDocument - Class in org.predict4all.nlp.trainer.corpus
AbstractTokenTrainingDocument(TrainingStep, File, File) - Constructor for class org.predict4all.nlp.trainer.corpus.AbstractTokenTrainingDocument
AbstractTrainingDocument - Class in org.predict4all.nlp.trainer.corpus
AbstractTrainingDocument(TrainingStep, String, File, File) - Constructor for class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
AbstractWord - Class in org.predict4all.nlp.words.model
AbstractWord(int) - Constructor for class org.predict4all.nlp.words.model.AbstractWord
ACCENTS - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
ACRONYM - org.predict4all.nlp.EquivalenceClass
AcronymMatcher - Class in org.predict4all.nlp.language.french.matcher
AcronymMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.AcronymMatcher
add(T) - Method in class org.predict4all.nlp.utils.FifoSet
ADD_LETTER - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
addAndReturnAdded(double) - Method in class org.predict4all.nlp.utils.SingleThreadDoubleAdder
addChild(CorrectionRuleNode) - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: Convenient method to add a child to this node.
This method is NOOP if CorrectionRuleNode.getType() is CorrectionRuleNodeType.LEAF
addCorrectionsFor(String, Map<BiIntegerKey, NextWord>, Set<Integer>) - Method in class org.predict4all.nlp.words.correction.WordCorrectionGenerator
addTo(Collection<CorrectionRule>) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Helper to add this correction rule to a collection (useful for chaining calls)
APOSTROPHE - org.predict4all.nlp.Separator
ApostropheMatcher - Class in org.predict4all.nlp.language.french.matcher
ApostropheMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.ApostropheMatcher
append(Token) - Method in class org.predict4all.nlp.io.TokenFileOutputStream
append(Token) - Method in interface org.predict4all.nlp.parser.TokenAppender
append(Token) - Method in class org.predict4all.nlp.parser.TokenListAppender
appendDebugInformationForCurrentPart(StringBuilder, Pair<StringBuilder, StringBuilder>, CachedPrecomputedCorrectionRule) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
appendDebugInformationForCurrentPart(StringBuilder, Pair<StringBuilder, StringBuilder>, CachedPrecomputedCorrectionRule) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
appendToCurrentPart(CharSequence) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
appendToCurrentPart(CharSequence) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
AZERTY_KEYBOARD - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType

B

BACKSLASH - org.predict4all.nlp.Separator
BaseWordDictionary - Interface in org.predict4all.nlp.language: A language specific dictionary : contains lower case words and their unigram frequencies.
BiIntegerKey - Class in org.predict4all.nlp.utils
build() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
build() - Method in class org.predict4all.nlp.trainer.DataTrainerResult.Builder
BUILD_DATE - Static variable in class org.predict4all.nlp.Predict4AllInfo
builder() - Static method in class org.predict4all.nlp.trainer.DataTrainerResult: Creates builder to build DataTrainerResult.

C

CachedPrecomputedCorrectionRule - Class in org.predict4all.nlp.words.correction: Cached version of a CorrectionRule : this rule is to meant to be directly used in WordCorrectionGenerator.
It only contains information and should not be modified once generated from a CorrectionRule
calculateGrownCapacity() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
call() - Method in class org.predict4all.nlp.trainer.TrainerTask
capacity() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Returns the capacity of the hash table.
capitalize(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
capture(String) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
changeCurrentPartTo(StringBuilder) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
changeCurrentPartTo(StringBuilder) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
checkChildrenLoading(FileChannel) - Method in class org.predict4all.nlp.ngram.trie.StaticNGramTrieNode: Check that children for this node are loaded.
If not, try to load children from the given fileChannel.
checkChildrenLoading(DynamicNGramTrieNode) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
checkChildrenLoading(StaticNGramTrieNode) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
checkChildrenLoading(T) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: To check that the children of a given node are loaded into memory (and can be used)
checkNull(T, String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils: Throws a IllegalArgumentException if a given object is null
children - Variable in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: Represent the children node for this node.
Each child is stored by its value (= word id) and represent the possible next value.
To save memory, the map is created on demand, so even if this node has children, the map can be null if children are not loaded yet.
childrenBackoffWeight - Variable in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: Backoff weight for this node children frequencies
childrenPosition - Variable in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: Contains the children nodes position in file.
Position in a FileChannel is a long type, but to save memory the value is stored as an int (trie file never contains more than Integer.MAX_VALUE byte)
clear() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Empties the collection.
clear() - Method in class org.predict4all.nlp.utils.FifoSet
clearNextCache() - Method in interface org.predict4all.nlp.parser.token.Token
clone() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
clone() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
clone(int) - Method in class org.predict4all.nlp.words.model.EquivalenceClassWord
clone(int) - Method in class org.predict4all.nlp.words.model.SimpleWord
clone(int) - Method in class org.predict4all.nlp.words.model.TagWord
clone(int) - Method in class org.predict4all.nlp.words.model.UserWord
clone(int) - Method in interface org.predict4all.nlp.words.model.Word: Create a clone of this word.
This allow duplication existing word, an new id should be provided.
close() - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
close() - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
close() - Method in class org.predict4all.nlp.parser.TokenListAppender
close() - Method in class org.predict4all.nlp.parser.TokenListProvider
CLOSE_HOOK - org.predict4all.nlp.Separator
COMMA - org.predict4all.nlp.Separator
compact() - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Compact the nodes in this dictionary (this will call AbstractNGramTrieNode.compact() on root)
compact() - Method in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: compact the children of this node (if this node has children)
compact() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Compresses the hashtable to the minimum prime size (as defined by PrimeFinder) that will hold all of the elements currently in the table.
compareTo(AbstractPredictionToCompute) - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
computeD(TrainingConfiguration) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Compute the optimal value for d (absolute discounting parameter).
Usually d is computed with formula :
D = C1 / (C1 + 2 * C2)
Where C1 = number of ngram with count == 1, and C2 = number of ngram with count == 2.
computeD(TrainingConfiguration) - Method in class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary
computeD(TrainingConfiguration) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
computeD(TrainingConfiguration) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
computeMaxSize(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Computes the values of maxSize.
computePrediction(WordDictionary) - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
computePrediction(WordDictionary) - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
computePrediction(WordDictionary) - Method in class org.predict4all.nlp.prediction.model.UniquePredictionToCompute
computeProbabilityForChildren(int, double[], boolean) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Compute frequency for this node using absolute discounting.
Compute this node frequency, backoff weight, and then compute the frequency for node children.
consumeFreeSlot - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
contains(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Searches the set for val
contains(T) - Method in class org.predict4all.nlp.utils.FifoSet
containsKey(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
containsUpperCase(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
containsValue(Object) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
containsWord(int) - Method in class org.predict4all.nlp.language.french.FrenchStopWordDictionary
containsWord(int) - Method in interface org.predict4all.nlp.language.StopWordDictionary
containsWord(String) - Method in interface org.predict4all.nlp.language.BaseWordDictionary
containsWord(String) - Method in class org.predict4all.nlp.language.french.FrenchBaseWordDictionary
convertWrittenYearToExactYear(int) - Static method in class org.predict4all.nlp.language.french.FrenchLanguageUtils
CoOccurrenceKey - Class in org.predict4all.nlp.semantic
CoOccurrenceKey(int, int) - Constructor for class org.predict4all.nlp.semantic.CoOccurrenceKey
correction - Variable in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
CorrectionRule - Class in org.predict4all.nlp.words.correction: This correction is the most convenient way to create correction rules as it allow direct modification and has helping methods.
The WordCorrectionGenerator will then generate CachedPrecomputedCorrectionRule to use this rule.
Note that a single builder instance can result in multiple correction rule : correction rule should never be directly configured by user as this correction rule is more understandable.
Correction rule work as the following : you define errors which are the part replaced, and replacements which are the part correcting errors.
CorrectionRuleNode - Class in org.predict4all.nlp.words.correction: The way to represent correction rule used in WordPredictor via WordCorrectionGenerator
Correction rule are represented as a tree where you can enable/disable whole part of it (e.g. disabling a parent node also disable its children).
Node are typed with CorrectionRuleNode.getType() so they can be CorrectionRuleNodeType.NODE or CorrectionRuleNodeType.LEAF.
Every node can technically contains CorrectionRuleNode.getCorrectionRule() but be aware that only CorrectionRuleNodeType.LEAF are taken into account by WordCorrectionGenerator
CorrectionRuleNode(CorrectionRuleNodeType) - Constructor for class org.predict4all.nlp.words.correction.CorrectionRuleNode
CorrectionRuleNodeType - Enum in org.predict4all.nlp.words.correction: Represent the type of a CorrectionRuleNode
count - Variable in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
COUNT_FORMAT - Static variable in class org.predict4all.nlp.words.WordDictionaryGenerator
countEndUntilNextSeparator(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
countNGram(int, int, AtomicInteger, AtomicInteger) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Count the number of ngram on a order : count the total count (occurence count) and the unique count (difference ngram count)
countNGrams() - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
countOneAndTwoOccurenceNGrams(int, AtomicInteger[], AtomicInteger[]) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Count the number of ngram with a count == 1 or == 2.
This ignore ngram containing Tag.START
countStartUntilNextSeparator(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
create(int) - Static method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary: Create an empty training ngram trie dictionary
create(int, String) - Static method in class org.predict4all.nlp.words.model.SimpleWord
create(int, String) - Static method in class org.predict4all.nlp.words.model.UserWord
create(int, String, double, boolean, boolean, long, int) - Static method in class org.predict4all.nlp.words.model.UserWord
create(String) - Static method in class org.predict4all.nlp.parser.token.WordToken
create(String, EquivalenceClass) - Static method in class org.predict4all.nlp.parser.token.EquivalenceClassToken
create(Separator) - Static method in class org.predict4all.nlp.parser.token.SeparatorToken
create(Tag) - Static method in class org.predict4all.nlp.parser.token.TagToken
createDouble(int, int, Separator, double, boolean, StringBuilder) - Static method in class org.predict4all.nlp.words.NextWord
createMap(T...) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
createMatchedString(List<String>) - Method in class org.predict4all.nlp.language.french.matcher.AcronymMatcher
createMatchedString(List<String>) - Method in class org.predict4all.nlp.language.french.matcher.HyphenMatcher
createMatchedString(List<String>) - Method in class org.predict4all.nlp.parser.matcher.AbstractRecursiveMatcher
createModified(int, String, boolean, boolean, double, boolean, boolean) - Static method in class org.predict4all.nlp.words.model.SimpleWord
createPrefixFor(List<Token>, WordPrefixDetected, int, boolean) - Method in class org.predict4all.nlp.ngram.NGramWordPredictorUtils: Create the prefix for a given raw context (token list) : the context is meant to be used for ngram trie exploring.
The context takes care of using only the last sentence, to detect the current written word, and to retrieve a context of the wanted order.
createUnique(int, double, boolean, StringBuilder) - Static method in class org.predict4all.nlp.words.NextWord
createWordDictionary(TrainingCorpus, Consumer<List<TrainerTask>>, File) - Method in class org.predict4all.nlp.words.WordDictionaryGenerator
CURRENCY_EURO_SYMBOL - org.predict4all.nlp.Separator
currentPartFinishedAndNewPartStarted(Separator, StringBuilder) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
currentPartFinishedAndNewPartStarted(Separator, StringBuilder) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
CUSTOM - org.predict4all.nlp.EquivalenceClass

D

DaemonThreadFactory - Class in org.predict4all.nlp.utils
DaemonThreadFactory() - Constructor for class org.predict4all.nlp.utils.DaemonThreadFactory
DataTrainer - Class in org.predict4all.nlp.trainer: Class to create prediction data to be used with a word predictor.
DataTrainer(File, File, File, File, LanguageModel, TrainingConfiguration) - Constructor for class org.predict4all.nlp.trainer.DataTrainer
DataTrainerResult - Class in org.predict4all.nlp.trainer
DataTrainerResult.Builder - Class in org.predict4all.nlp.trainer: Builder to build DataTrainerResult.
DATE_DAY_MONTH - org.predict4all.nlp.EquivalenceClass
DATE_FULL_DIGIT - org.predict4all.nlp.EquivalenceClass
DATE_FULL_TEXT - org.predict4all.nlp.EquivalenceClass
DATE_HOUR - org.predict4all.nlp.EquivalenceClass
DATE_MONTH - org.predict4all.nlp.EquivalenceClass
DATE_MONTH_YEAR - org.predict4all.nlp.EquivalenceClass
DATE_WEEK_DAY - org.predict4all.nlp.EquivalenceClass
DateDayMonthMatcher - Class in org.predict4all.nlp.language.french.matcher
DateDayMonthMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.DateDayMonthMatcher
DateFullDigitMatcher - Class in org.predict4all.nlp.language.french.matcher
DateFullDigitMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.DateFullDigitMatcher
DateFullTextMatcher - Class in org.predict4all.nlp.language.french.matcher
DateFullTextMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.DateFullTextMatcher
DateMonthYearMatcher - Class in org.predict4all.nlp.language.french.matcher
DateMonthYearMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.DateMonthYearMatcher
DateWeekDayMatcher - Class in org.predict4all.nlp.language.french.matcher
DateWeekDayMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.DateWeekDayMatcher
debug(WordDictionary, AbstractNGramTrieNode<?>) - Method in interface org.predict4all.nlp.ngram.debug.NGramDebugger
debugInformation - Variable in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
DECIMAL - org.predict4all.nlp.EquivalenceClass
defaultConfiguration() - Static method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
defaultConfiguration(File) - Static method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
DICTIONARY_INFORMATION_BYTE_COUNT - Static variable in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Byte count needed to save general information about this dictionary.
dispose() - Method in class org.predict4all.nlp.prediction.WordPredictor: Try to close/dispose word predictor resources.
This will close ngram dictionary and dynamic dictionary (equivalent to call AutoCloseable.close() on both) and also the WordCorrectionGenerator if it was enabled.
dispose() - Method in class org.predict4all.nlp.words.correction.WordCorrectionGenerator
document - Variable in class org.predict4all.nlp.trainer.TrainerTask
DOUBLE_LETTER - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
DoublePredictionToCompute - Class in org.predict4all.nlp.prediction.model: Represent the prediction for two word in a row.
Could have been generic (more than two, but for computing performance, limit combination to two word only)
DoublePredictionToCompute(int, int, boolean, int[], int[], double, boolean, StringBuilder) - Constructor for class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
DYNAMIC_TRIE_NODE_SIZE_BYTE - Static variable in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: Dynamic node byte size (4 integer) Integer : word id, children size, children position, count
DynamicNGramDictionary - Class in org.predict4all.nlp.ngram.dictionary: Represent a TrainingNGramDictionary that can also be opened to be trained again.
This type of dictionary is useful when using a dynamic user model : the dynamic user dictionary is loaded and trained during each session, and then saved to be used in the next sessions.
DynamicNGramDictionary(int) - Constructor for class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary
DynamicNGramTrieNode - Class in org.predict4all.nlp.ngram.trie: Represent a dynamic trie node structure : this trie node is useful when the ngram count has to be retrieved.
Dynamic trie node children are always fully loaded (they are not loaded on demand) and their frequencies can change.
Because dynamic trie node are used to be saved and loaded as StaticNGramTrieNode or DynamicNGramTrieNode they contains two write method : DynamicNGramTrieNode.writeStaticNode(FileChannel, int) if they are saved to be loaded as StaticNGramTrieNode and DynamicNGramTrieNode.writeDynamicNode(FileChannel, int) if they are saved to be loaded as DynamicNGramTrieNode : one save static information about the node (frequency, bow), the other only save dynamic information (count) because frequencies are dynamically computed.
DynamicNGramTrieNode() - Constructor for class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode

E

encoding - Variable in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
endCorrection(double) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
endCorrection(double) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
endsWith(String, String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
EQUAL - org.predict4all.nlp.Separator
equals(Object) - Method in class org.predict4all.nlp.ngram.NGramKey
equals(Object) - Method in class org.predict4all.nlp.parser.token.SeparatorToken
equals(Object) - Method in class org.predict4all.nlp.parser.token.WordToken
equals(Object) - Method in class org.predict4all.nlp.semantic.CoOccurrenceKey
equals(Object) - Method in class org.predict4all.nlp.utils.BiIntegerKey
equals(Object) - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
EquivalenceClass - Enum in org.predict4all.nlp: Represent a equivalence class type that can be used when training a language model.
Useful to group same kind of element in a corpus under a same concept instead of textual data.
3 These are especially used in semantic data.
EquivalenceClassToken - Class in org.predict4all.nlp.parser.token
EquivalenceClassWord - Class in org.predict4all.nlp.words.model
EquivalenceClassWord(EquivalenceClass) - Constructor for class org.predict4all.nlp.words.model.EquivalenceClassWord
EXCLAMATION - org.predict4all.nlp.Separator
executeLSATrainingForR(TrainingCorpus, File, Consumer<List<? extends TrainerTask>>) - Method in class org.predict4all.nlp.semantic.SemanticDictionaryGenerator
executeNGramTraining(TrainingCorpus, File, Consumer<List<TrainerTask>>) - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
executeTermDetection(List<Token>) - Method in class org.predict4all.nlp.parser.matcher.TokenConverter
executeTokenPatternMatching(TrainingCorpus) - Method in class org.predict4all.nlp.parser.matcher.TokenConverter
executeWriteLevelOnRoot(FileChannel, int) - Method in class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary
executeWriteLevelOnRoot(FileChannel, int) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary: Call the correct node method to save a trie level to file.
exploreChildren(int, int, BiConsumer<Integer, DynamicNGramTrieNode>) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode

F

factor - Variable in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
FifoSet<T> - Class in org.predict4all.nlp.utils: A set maintaining exactly FifoSet.maxSize or less but keeping there insertion order to always delete the first inserted element when set is full.
FifoSet(int) - Constructor for class org.predict4all.nlp.utils.FifoSet
FILENAME_LSA_DICTIONARY - Static variable in class org.predict4all.nlp.trainer.DataTrainer
FILENAME_NGRAM_DICTIONARY - Static variable in class org.predict4all.nlp.trainer.DataTrainer
FILENAME_WORD_DICTIONARY - Static variable in class org.predict4all.nlp.trainer.DataTrainer
forceInvalid - Variable in class org.predict4all.nlp.words.model.SimpleWord
forceValid - Variable in class org.predict4all.nlp.words.model.SimpleWord
forEach(TIntProcedure) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Executes procedure for each element in the set.
forEachEntry(TIntObjectProcedure<? super V>) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
forEachKey(TIntProcedure) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
forEachValue(TObjectProcedure<? super V>) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
forEachValue(Consumer<? super V>) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
FOUR_DIGIT_FORMAT_ALWAYS - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageUtils
FREE - Static variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: flag indicating that a slot in the hashtable is available
FrenchBaseWordDictionary - Class in org.predict4all.nlp.language.french: French dictionary based on Lexique.org
FrenchBaseWordDictionary(String) - Constructor for class org.predict4all.nlp.language.french.FrenchBaseWordDictionary
FrenchDefaultCorrectionRuleGenerator - Class in org.predict4all.nlp.language.french: Generate base correction rule for french language.
Keep every possible rule in FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType with a translated name, description and example.
FrenchDefaultCorrectionRuleGenerator() - Constructor for class org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator
FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType - Enum in org.predict4all.nlp.language.french
FrenchDefaultCorrectionRuleGenerator.TranslationProvider - Interface in org.predict4all.nlp.language.french
FrenchLanguageModel - Class in org.predict4all.nlp.language.french
FrenchLanguageModel() - Constructor for class org.predict4all.nlp.language.french.FrenchLanguageModel
FrenchLanguageUtils - Class in org.predict4all.nlp.language.french: Utils methods for french language.
FrenchStopWordDictionary - Class in org.predict4all.nlp.language.french
FrenchStopWordDictionary(String) - Constructor for class org.predict4all.nlp.language.french.FrenchStopWordDictionary
frequency - Variable in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: Computed frequency for this node
from(TrainingConfiguration) - Static method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
FULL - Static variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: flag indicating that a slot in the hashtable is occupied

G

GE_GU_SOUND - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
generateNodeFor(PredictionParameter) - Method in enum org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
GeneratingCorrectionI - Interface in org.predict4all.nlp.words.correction
get(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
getAbbreviationOrRegex() - Static method in class org.predict4all.nlp.language.french.FrenchLanguageUtils
getAllWords() - Method in class org.predict4all.nlp.words.WordDictionary: All the existing words in this dictionary.
Words can be special words as TagWord, EquivalenceClassWord, etc.
They can also be SimpleWord from a trained model, and UserWord if they are word "learned" when using the predictor.
Note that if you ony want the possible words for final user, you should use Word.isValidToBePredicted(PredictionParameter) to filter out invalid words.
getAverageVocabularySize() - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getAverageVocabularySize() - Method in interface org.predict4all.nlp.language.LanguageModel: Average total vocabulary size (different existing words)
getAverageWordLength() - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getAverageWordLength() - Method in interface org.predict4all.nlp.language.LanguageModel
getBaseWordDictionary(TrainingConfiguration) - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getBaseWordDictionary(TrainingConfiguration) - Method in interface org.predict4all.nlp.language.LanguageModel
getBaseWordDictionaryPath() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getById(byte) - Static method in enum org.predict4all.nlp.Tag
getChildren() - Method in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode
getChildren() - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: This node children, only useful if CorrectionRuleNode.getType() is CorrectionRuleNodeType.NODE
getChildrenBackoffWeight() - Method in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode
getChildrenCountSum() - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode
getChildrenSize() - Method in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode
getChildrenSize() - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode
getChildrenSize() - Method in class org.predict4all.nlp.ngram.trie.StaticNGramTrieNode
getConcurrencyLevel() - Method in class org.predict4all.nlp.trainer.corpus.TrainingCorpus
getConvertCaseFromDictionaryModelThreshold() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getCorpus() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getCorrectionDefaultCost() - Method in class org.predict4all.nlp.prediction.PredictionParameter: The default cost applied to correction rule if CorrectionRule.getCost() is null.
getCorrectionDefaultFactor() - Method in class org.predict4all.nlp.prediction.PredictionParameter: The default factor applied to correction rule if CorrectionRule.getFactor() is null.
getCorrectionMaxCost() - Method in class org.predict4all.nlp.prediction.PredictionParameter: Determine how much correction will be applied to a same input.
The higher this value, the more correction will be applied.
getCorrectionRule() - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: The correction rule associated on this node.
Will be taken into account only if CorrectionRuleNode.getType() is CorrectionRuleNodeType.LEAF
getCorrectionRulesRoot() - Method in class org.predict4all.nlp.prediction.PredictionParameter: The correction rules to apply if PredictionParameter.isEnableWordCorrection() is enabled.
Correction rule are organised as a tree to allow enabling/disabled a whole part of the tree.
Correction rules can be created programmatically, or FrenchDefaultCorrectionRuleGenerator can be used.
getCost() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getCost() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: The correction cost will influence how many correction are cumulated for a same input.
Typically, correction costs are added to check that they are bellow PredictionParameter.getCorrectionMaxCost()
getCount() - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode
getCount() - Method in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
getCount() - Method in class org.predict4all.nlp.utils.progressindicator.LoggingProgressIndicator
getCount() - Method in class org.predict4all.nlp.utils.progressindicator.NoOpProgressIndicator
getCount() - Method in interface org.predict4all.nlp.utils.progressindicator.ProgressIndicator
getCountMap() - Method in class org.predict4all.nlp.utils.FifoSet
getCurrentPart() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getCurrentPart() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getCurrentPartLength() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getCurrentPartLength() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getCustomParameters() - Method in class org.predict4all.nlp.prediction.PredictionParameter: Free to use String,String map to had your custom parameters.
This is just a helper as PredictionParameter can be loaded/saved with PredictionParameter.saveTo(File) and PredictionParameter.loadFrom(LanguageModel, File) It allows you to add your custom prediction relative configuration parameter without having to save them in a different file
getDebugInformation() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
getDebugInformation() - Method in class org.predict4all.nlp.prediction.WordPrediction
getDebugInformation() - Method in class org.predict4all.nlp.prediction.WordPredictionResult
getDebugInformation() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getDebugInformation() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getDebugInformation() - Method in class org.predict4all.nlp.words.NextWord
getDebugPrefix() - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
getDebugPrefix() - Method in class org.predict4all.nlp.trainer.DataTrainer
getDensitiesMap() - Method in class org.predict4all.nlp.semantic.SemanticDictionary
getDescriptionId() - Method in enum org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
getDirectlyValidWordCountThreshold() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getDocuments(TrainingStep) - Method in class org.predict4all.nlp.trainer.corpus.TrainingCorpus
getDynamicModelMinimumWeight() - Method in class org.predict4all.nlp.prediction.PredictionParameter: Useful to set the minimum weight for dynamic model when interpolating both static and dynamic model.
Value should ranger between 0.0 and 0.5.
getDynamicNGramDictionary() - Method in class org.predict4all.nlp.prediction.WordPredictor
getECById(byte) - Static method in enum org.predict4all.nlp.EquivalenceClass
getEncoding() - Method in class org.predict4all.nlp.trainer.corpus.TrainingCorpus
getEndFactor() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getEndFactor() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getEndPart(int) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getEndPart(int) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getEndSeparator(int) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getEndSeparator(int) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getEndUntilNextSeparator(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
getEquivalenceClass() - Method in class org.predict4all.nlp.parser.token.EquivalenceClassToken
getEquivalenceClass() - Method in interface org.predict4all.nlp.parser.token.Token
getEquivalenceClass() - Method in class org.predict4all.nlp.words.model.AbstractWord
getEquivalenceClass() - Method in interface org.predict4all.nlp.words.model.Word
getEquivalenceClassId() - Method in class org.predict4all.nlp.words.model.AbstractWord
getEquivalenceClassId() - Method in class org.predict4all.nlp.words.model.EquivalenceClassWord
getEquivalenceClassId() - Method in interface org.predict4all.nlp.words.model.Word
getError() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getErrors() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Determine the errors for this correction rule.
Error define the part of the text that could be replaced.
For example, if error is "a", every "a" char in user input could be potnetially replaced with CorrectionRule.withReplacement(String...) Errors should not contains any word separator(space, etc...)
getExactWordsWithPrefixExist(String) - Method in class org.predict4all.nlp.words.WordDictionary
getExampleId() - Method in enum org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
getExtractedTokenValues() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexResult
getExtractedValue(int) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexResult
getFactor() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
getFactor() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getFactor() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: The correction factor will influence how much the correction "counts" relatively to a correct word.
getFactor() - Method in class org.predict4all.nlp.words.NextWord
getFirstPrefix() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
getFirstWordId() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
getFormattedText() - Method in class org.predict4all.nlp.parser.matcher.PatternMatched
getFrequency() - Method in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode
getFrequency(String) - Method in interface org.predict4all.nlp.language.BaseWordDictionary
getFrequency(String) - Method in class org.predict4all.nlp.language.french.FrenchBaseWordDictionary
getId() - Method in enum org.predict4all.nlp.EquivalenceClass
getId() - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getId() - Method in interface org.predict4all.nlp.language.LanguageModel
getId() - Method in enum org.predict4all.nlp.Separator
getId() - Method in enum org.predict4all.nlp.Tag
getID() - Method in class org.predict4all.nlp.words.model.AbstractWord
getID() - Method in interface org.predict4all.nlp.words.model.Word
getIdByte() - Method in enum org.predict4all.nlp.EquivalenceClass
getIdByte() - Method in enum org.predict4all.nlp.Separator
getIdByte() - Method in enum org.predict4all.nlp.Tag
getInputFile() - Method in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
getKey() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getKey() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getLanguageModel() - Method in class org.predict4all.nlp.prediction.PredictionParameter: The language model to be used to predict words.
Typically implementations are provided by the framework (see FrenchLanguageModel)
It should always be filled
getLastMatchedToken() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexResult
getLastUseDate() - Method in class org.predict4all.nlp.words.model.AbstractWord
getLastUseDate() - Method in class org.predict4all.nlp.words.model.UserWord
getLastUseDate() - Method in interface org.predict4all.nlp.words.model.Word
getLeft() - Method in class org.predict4all.nlp.utils.Pair
getLeft() - Method in class org.predict4all.nlp.utils.Triple
getLongestMatchingWords(List<Token>, int, Set<Integer>) - Method in class org.predict4all.nlp.words.WordPrefixDetector: Try to detect if the end of the given sentence finish with a word already started.
This is much more precise than just checking if the last token is a separator, because a word could have separator inside (e.g. : "New York" has a space, "là-bas" has a hyphen).
getLongestWordPrefix() - Method in class org.predict4all.nlp.words.WordPrefixDetected
getLsaDensitySize() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getLsaFrequentWordSize() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getLsaTargetSvdSize() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getLsaVocabularySize() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getLsaWindowSize() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getMax() - Method in class org.predict4all.nlp.utils.progressindicator.LoggingProgressIndicator
getMax() - Method in class org.predict4all.nlp.utils.progressindicator.NoOpProgressIndicator
getMax() - Method in interface org.predict4all.nlp.utils.progressindicator.ProgressIndicator
getMaxIdValue() - Static method in enum org.predict4all.nlp.EquivalenceClass
getMaxIndexFromEnd() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getMaxIndexFromEnd() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Max index (from word end), exclusive (e.g. maxIndexFromEnd = 2, never apply the rule on the last two char)
Useful to ignore word ends.
getMaxIndexFromStart() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getMaxIndexFromStart() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Max index (from word start), exclusive (e.g. maxIndexFromStart = 1, only the first char)
Useful to restrain correction to the word start.
getMaxOrder() - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary
getMiddle() - Method in class org.predict4all.nlp.utils.Triple
getMinCountToProvideCorrection() - Method in class org.predict4all.nlp.prediction.PredictionParameter: A minimum count of char before having correction result integrated.
Note that this has not effect if PredictionParameter.isEnableWordCorrection() is disabled.
Typically, setting this value to 3 will allow predictor to check for correction only once user typed 3 chars.
getMinCountToProvidePrediction() - Method in class org.predict4all.nlp.prediction.PredictionParameter: A minimum count of char before having prediction result.
This built-in feature allow prediction to be displayed only after a certain amount of user input.
Typically, setting this value to 1 will disable next word prediction and will only predict current typed word prediction.
getMinIndexFromEnd() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getMinIndexFromEnd() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Min index, from end, inclusive (inclusive from word end, e.g. if = 1, only correct the last char)
Useful to correct only the last part of a word.
getMinIndexFromStart() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getMinIndexFromStart() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Min index, from start, inclusive (inclusive from word start, e.g. if = 1, never correct the first char)
Useful to correct only the "middle" area of a word
getMinUseCountToValidateNewWord() - Method in class org.predict4all.nlp.prediction.PredictionParameter: Minimum new word use count to be displayed in the prediction.
This avoid having typing errors displayed as prediction results.
getMonthOrRegex() - Static method in class org.predict4all.nlp.language.french.FrenchLanguageUtils
getName() - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: The name for this node (just informative)
getNameId() - Method in enum org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
getNext() - Method in class org.predict4all.nlp.io.TokenFileInputStream
getNext() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher
getNext() - Method in class org.predict4all.nlp.parser.TokenListProvider
getNext() - Method in interface org.predict4all.nlp.parser.TokenProvider
getNext(TokenProvider) - Method in interface org.predict4all.nlp.parser.token.Token
getNextCharCountToRemove() - Method in class org.predict4all.nlp.prediction.WordPredictionResult
getNextWord(int[]) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Return the immediate next words for a given prefix (without any filter)
getNgramCounts() - Method in class org.predict4all.nlp.trainer.DataTrainerResult
getNgramDebugAfterPruning() - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
getNgramDebugBeforePruning() - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
getNgramOrder() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getNgramPruningCountThreshold() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getNgramPruningOrderCountThresholds() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getNgramPruningWeightedDifferenceThreshold() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getNGramTag() - Method in class org.predict4all.nlp.words.model.AbstractWord
getNGramTag() - Method in interface org.predict4all.nlp.words.model.Word
getNGramTagId() - Method in class org.predict4all.nlp.words.model.AbstractWord
getNGramTagId() - Method in class org.predict4all.nlp.words.model.TagWord
getNGramTagId() - Method in interface org.predict4all.nlp.words.model.Word
getNodeFor(int[], int, int) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Retrieve a node for a given prefix (if exists)
getNodeFor(FileChannel, int[], int) - Method in class org.predict4all.nlp.ngram.trie.StaticNGramTrieNode: Will try to retrieve a node for a given prefix.
Load needed node on demand while browsing the trie.
Children of the returned node are not loaded yet.
getNodeForPrefix(int[], int) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Use to retrieve a node for a given prefix.
For example, for prefix = [1,2] will return the trie node corresponding to {2}.
The children of the given node may have not been loaded.
getNodeForPrefix(int[], int) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
getNodeForPrefix(int[], int) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
getOfficialChar() - Method in enum org.predict4all.nlp.Separator
getOfficialCharString() - Method in enum org.predict4all.nlp.Separator
getOrDefault(T, T) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
getOutputDirectory() - Method in class org.predict4all.nlp.trainer.corpus.TrainingCorpus
getOutputDirectoryName() - Method in enum org.predict4all.nlp.trainer.step.TrainingStep
getOutputFile() - Method in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
getPartCount() - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
getPartCount() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
getPattern(String, int) - Static method in class org.predict4all.nlp.parser.matcher.TermMatcherUtils
getPrediction() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
getPredictionParameter() - Method in class org.predict4all.nlp.prediction.WordPredictor
getPredictions() - Method in class org.predict4all.nlp.prediction.WordPredictionResult
getPredictionToDisplay() - Method in class org.predict4all.nlp.prediction.WordPrediction
getPredictionToInsert() - Method in class org.predict4all.nlp.prediction.WordPrediction
getPreviousCharCountToRemove() - Method in class org.predict4all.nlp.prediction.WordPrediction
getPreviousEndToken() - Method in class org.predict4all.nlp.parser.matcher.PatternMatched
getPreviousStep() - Method in enum org.predict4all.nlp.trainer.step.TrainingStep
getProbability(int[], int, int, int) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Return the probability of a word for a given prefix.
Given index = 0 and length = prefix.length will return the maximum order probability (e.g. prefix.length = 3, will return probability for order 3)
getProbFactor() - Method in class org.predict4all.nlp.words.model.AbstractWord
getProbFactor() - Method in class org.predict4all.nlp.words.model.SimpleWord
getProbFactor() - Method in interface org.predict4all.nlp.words.model.Word: This factor can be used to modify final probabilities of the predictions.
It will be applied once probabilities are computed to influence result list.
It is mainly used in a multiplication with the original probability (and then the result list is normalized).
To only rely on probabilities, the value should be 1.0
getPruningMethod() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getRawProbability(int[], int, int, int) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary
getRegex() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher
getReplacement() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getReplacementLeftPart() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getReplacementRightPart() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getReplacements() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Determine the replacements that could be used to correct the CorrectionRule.getErrors().
Replacement could contains at most one word separator (space, etc...) : this allow correction merged words.
getReplacementSeparator() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getReplacementSeparatorIndex() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getRight() - Method in class org.predict4all.nlp.utils.Pair
getRight() - Method in class org.predict4all.nlp.utils.Triple
getRoot() - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary
getRootBlockSize() - Method in class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary
getRootBlockSize() - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
getScore() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
getScore() - Method in class org.predict4all.nlp.prediction.WordPrediction
getSecondPrefix() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
getSecondWordId() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
getSemanticContrastFactor() - Method in interface org.predict4all.nlp.semantic.SemanticDictionaryConfiguration
getSemanticDensityMaxBound() - Method in interface org.predict4all.nlp.semantic.SemanticDictionaryConfiguration
getSemanticDensityMinBound() - Method in interface org.predict4all.nlp.semantic.SemanticDictionaryConfiguration
getSeparator() - Method in class org.predict4all.nlp.parser.token.SeparatorToken
getSeparator() - Method in interface org.predict4all.nlp.parser.token.Token
getSeparator() - Method in class org.predict4all.nlp.words.NextWord
getSeparatorById(byte) - Static method in enum org.predict4all.nlp.Separator
getSeparatorFor(char) - Static method in enum org.predict4all.nlp.Separator
getSet() - Method in class org.predict4all.nlp.utils.FifoSet
getSimilarityCosineFor(Collection<Integer>, List<AbstractPredictionToCompute>, double) - Method in class org.predict4all.nlp.semantic.SemanticDictionary
getSmoothingDiscountValue() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getSmoothingDiscountValueLowerBound() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getSmoothingDiscountValueUpperBound() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getSrcBuilder() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
getStartUntilNextSeparator(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
getStaticNgramDictionary() - Method in class org.predict4all.nlp.prediction.WordPredictor
getStep() - Method in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
getStep(File, TrainingCorpus) - Method in enum org.predict4all.nlp.trainer.step.TrainingStep
getStopWordDictionary(TrainingConfiguration) - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getStopWordDictionary(TrainingConfiguration) - Method in interface org.predict4all.nlp.language.LanguageModel
getStopWordDictionaryPath() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getTag() - Method in class org.predict4all.nlp.parser.token.TagToken
getTag() - Method in interface org.predict4all.nlp.parser.token.Token
getText() - Method in class org.predict4all.nlp.parser.token.SeparatorToken
getText() - Method in interface org.predict4all.nlp.parser.token.Token
getText() - Method in class org.predict4all.nlp.parser.token.WordToken
getTextForType() - Method in interface org.predict4all.nlp.parser.token.Token
getTokenCount() - Method in class org.predict4all.nlp.words.WordPrefixDetected
getTokenMatchersForNGram() - Method in class org.predict4all.nlp.language.AbstractLanguageModel
getTokenMatchersForNGram() - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getTokenMatchersForNGram() - Method in interface org.predict4all.nlp.language.LanguageModel
getTokenMatchersForSemanticAnalysis() - Method in class org.predict4all.nlp.language.AbstractLanguageModel
getTokenMatchersForSemanticAnalysis() - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getTokenMatchersForSemanticAnalysis() - Method in interface org.predict4all.nlp.language.LanguageModel
getTotalCountFor(TrainingStep) - Method in class org.predict4all.nlp.trainer.corpus.TrainingCorpus
getType() - Method in class org.predict4all.nlp.parser.matcher.PatternMatched
getType() - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: Type of this node
getType() - Method in class org.predict4all.nlp.words.model.EquivalenceClassWord
getType() - Method in class org.predict4all.nlp.words.model.SimpleWord
getType() - Method in class org.predict4all.nlp.words.model.TagWord
getType() - Method in class org.predict4all.nlp.words.model.UserWord
getType() - Method in interface org.predict4all.nlp.words.model.Word
getUnknownWordCountThreshold() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getUpperCaseReplacementThreshold() - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
getUsageCount() - Method in class org.predict4all.nlp.words.model.AbstractWord
getUsageCount() - Method in class org.predict4all.nlp.words.model.UserWord
getUsageCount() - Method in interface org.predict4all.nlp.words.model.Word
getValidOneCharWords() - Method in class org.predict4all.nlp.language.AbstractLanguageModel
getValidOneCharWords() - Method in class org.predict4all.nlp.language.french.FrenchLanguageModel
getValidOneCharWords() - Method in interface org.predict4all.nlp.language.LanguageModel
getValidWordForPredictionByPrefix(String, PredictionParameter, int, Set<Integer>) - Method in class org.predict4all.nlp.words.WordDictionary: Returns all the words that starts with a given prefix.
The returned list is not sorted.
getWeekDaysOrRegex() - Static method in class org.predict4all.nlp.language.french.FrenchLanguageUtils
getWord() - Method in class org.predict4all.nlp.words.model.EquivalenceClassWord
getWord() - Method in class org.predict4all.nlp.words.model.SimpleWord
getWord() - Method in class org.predict4all.nlp.words.model.TagWord
getWord() - Method in interface org.predict4all.nlp.words.model.Word
getWord(int) - Method in class org.predict4all.nlp.words.WordDictionary: To get a word entity from id.
Contrary to other WordDictionary.getWord(String) method, this return null if there is no word for the given ID
getWord(String) - Method in class org.predict4all.nlp.words.WordDictionary: To get the word entity from text.
Note that this method will never return null : it can however return Tag.UNKNOWN id if there is no word in the dictionary for the given text.
getWordDictionary() - Method in class org.predict4all.nlp.prediction.WordPredictor
getWordId() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
getWordId() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
getWordId() - Method in class org.predict4all.nlp.prediction.model.UniquePredictionToCompute
getWordId() - Method in class org.predict4all.nlp.prediction.WordPrediction
getWordId(String) - Method in class org.predict4all.nlp.words.WordDictionary: To get a word ID.
Note that this method will never return null : it can however return Tag.UNKNOWN id if there is no word in the dictionary for the given text.
getWordId(WordDictionary) - Method in interface org.predict4all.nlp.parser.token.Token
getWordId1() - Method in class org.predict4all.nlp.words.NextWord
getWordId2() - Method in class org.predict4all.nlp.words.NextWord
getWords() - Method in class org.predict4all.nlp.words.WordPrefixDetected
getWordUsed() - Method in class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary

H

HASH - org.predict4all.nlp.Separator
hashCode() - Method in class org.predict4all.nlp.ngram.NGramKey
hashCode() - Method in class org.predict4all.nlp.parser.token.SeparatorToken
hashCode() - Method in class org.predict4all.nlp.parser.token.WordToken
hashCode() - Method in class org.predict4all.nlp.semantic.CoOccurrenceKey
hashCode() - Method in class org.predict4all.nlp.utils.BiIntegerKey
hashCode() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
hasNext() - Method in interface org.predict4all.nlp.parser.StringProducer
HEARING_CONFUSION - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
HOMOPHONE - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
HYPHEN - org.predict4all.nlp.Separator
HyphenMatcher - Class in org.predict4all.nlp.language.french.matcher: Term matcher to match word sequence with hyphen between each word.
The sequence should start and end with hyphen, examples : a-t : valid a-t-elle : valid a-t-elle- : not valid -test- : not valid
HyphenMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.HyphenMatcher

I

increment() - Method in class org.predict4all.nlp.utils.progressindicator.LoggingProgressIndicator
increment() - Method in class org.predict4all.nlp.utils.progressindicator.NoOpProgressIndicator
increment() - Method in interface org.predict4all.nlp.utils.progressindicator.ProgressIndicator
incrementUsageCount() - Method in class org.predict4all.nlp.words.model.AbstractWord
incrementUsageCount() - Method in class org.predict4all.nlp.words.model.UserWord
incrementUsageCount() - Method in interface org.predict4all.nlp.words.model.Word: To increase the "usage" count of this word
incrementUserWord(int) - Method in class org.predict4all.nlp.words.WordDictionary
index(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Locates the index of val.
indexOfInCurrentPart(String, int) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
indexOfInCurrentPart(String, int) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
INF_SUP - org.predict4all.nlp.Separator
INFO_EXTENSION - Static variable in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
initialize() - Method in interface org.predict4all.nlp.language.BaseWordDictionary
initialize() - Method in class org.predict4all.nlp.language.french.FrenchBaseWordDictionary
initialize(WordDictionary) - Method in class org.predict4all.nlp.language.french.FrenchStopWordDictionary
initialize(WordDictionary) - Method in interface org.predict4all.nlp.language.StopWordDictionary
initializeInformation() - Method in class org.predict4all.nlp.trainer.corpus.AbstractTokenTrainingDocument
initializeInformation() - Method in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
initializeInformation() - Method in class org.predict4all.nlp.trainer.step.ParserTrainingDocument
initStep(TrainingStep) - Method in class org.predict4all.nlp.trainer.corpus.TrainingCorpus
inputFile - Variable in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
insertKey(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Locates the index at which val can be inserted. if there is already a value equal()ing val in the set, returns that value as a negative integer.
INSTANCE - Static variable in class org.predict4all.nlp.utils.progressindicator.NoOpProgressIndicator
INTEGER - org.predict4all.nlp.EquivalenceClass
isAddNewWordsEnabled() - Method in class org.predict4all.nlp.prediction.PredictionParameter: Enable/disable that new words can be added to dictionary while using the word predictor or while training the dynamic model.
Note that added word could appears in predictions only if they appeared enough times, as suggestion by PredictionParameter.getMinUseCountToValidateNewWord()
isBidirectional() - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Bidirectional indicate that the resulting rule will be acting in both way : errors will be replaced with replacements and replacements will be replaced with errors.
This is quite the same as CorrectionRule.withConfusionSet(String...) with a difference is that in a confusion set, errors can be replaced by errors and replacements can be replaced with replacements, which is not the case in bidirectional rules.
If you have only one error and replacement, confusion set and bidirectional will result in the same rule.
isBlank(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
isCapitalized(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
isCapitalizedWord() - Method in class org.predict4all.nlp.words.WordPrefixDetected
isCaptureValue() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher
isCorrection() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
isCorrection() - Method in class org.predict4all.nlp.prediction.WordPrediction
isCorrection() - Method in class org.predict4all.nlp.words.NextWord
isDouble() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
isDouble() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
isDouble() - Method in class org.predict4all.nlp.prediction.model.UniquePredictionToCompute
isDouble() - Method in class org.predict4all.nlp.words.NextWord
isDynamicModelEnabled() - Method in class org.predict4all.nlp.prediction.PredictionParameter: Enable/disable the use of dynamic model when predicting next words.
If enabled, it should always be combined with an instance of DynamicNGramDictionary given to WordPredictor.
The model can be trained via the WordPredictor.trainDynamicModel(String, boolean)
isEmpty() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Tells whether this set is currently holding any elements.
isEmpty(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
isEnabled() - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: To know if this node should be taken into account in WordCorrectionGenerator
Note that individually node can be enabled but then ignored.
isEnableDebugInformation() - Method in class org.predict4all.nlp.prediction.PredictionParameter: To enable debug information while predictor is working.
This should be enabled carefully : debug is expensive in memory and computing cost as it creates a lot of String instance.
Typically this should never be enabled when using the predictor in production.
Enabling debug will fill WordPredictionResult.getDebugInformation() and WordPrediction.getDebugInformation()
isEnableWordCorrection() - Method in class org.predict4all.nlp.prediction.PredictionParameter: To enable/disable word correction.
Enabling this parameter will use PredictionParameter.getCorrectionRulesRoot() to determine the rules to be used by the correction algorithms.
isEquivalenceClass() - Method in class org.predict4all.nlp.parser.token.EquivalenceClassToken
isEquivalenceClass() - Method in interface org.predict4all.nlp.parser.token.Token
isEquivalenceClass() - Method in class org.predict4all.nlp.words.model.AbstractWord
isEquivalenceClass() - Method in interface org.predict4all.nlp.words.model.Word
isForceInvalid() - Method in class org.predict4all.nlp.words.model.AbstractWord
isForceInvalid() - Method in class org.predict4all.nlp.words.model.SimpleWord
isForceInvalid() - Method in interface org.predict4all.nlp.words.model.Word: To force that this word is invalid.
In fact, this method allow removal of a word from prediction result : words can't be removed from dictionary as they can be used in ngrams, but having forceInvalid true has the same effect than removing a word.
isForceValid() - Method in class org.predict4all.nlp.words.model.AbstractWord
isForceValid() - Method in class org.predict4all.nlp.words.model.SimpleWord
isForceValid() - Method in interface org.predict4all.nlp.words.model.Word: To force that this word become valid, mostly use on UserWord to ignore validation.
isFullUpperCase(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
isInitialized() - Method in interface org.predict4all.nlp.language.BaseWordDictionary
isInitialized() - Method in class org.predict4all.nlp.language.french.FrenchBaseWordDictionary
isInitialized() - Method in class org.predict4all.nlp.language.french.FrenchStopWordDictionary
isInitialized() - Method in interface org.predict4all.nlp.language.StopWordDictionary
isInsertSpacePossible() - Method in class org.predict4all.nlp.prediction.WordPrediction
isModifiedBySystem() - Method in class org.predict4all.nlp.words.model.AbstractWord
isModifiedBySystem() - Method in class org.predict4all.nlp.words.model.SimpleWord
isModifiedBySystem() - Method in interface org.predict4all.nlp.words.model.Word: Indicate that this word was modified by the system (e.g. calling a modification method with modificationByUser parameter to false)
isModifiedByUser() - Method in class org.predict4all.nlp.words.model.AbstractWord
isModifiedByUser() - Method in class org.predict4all.nlp.words.model.SimpleWord
isModifiedByUser() - Method in interface org.predict4all.nlp.words.model.Word: Indicate that this word was modified by the user (e.g. calling a modification method with modificationByUser parameter to true)
isModifiedByUserOrSystem() - Method in class org.predict4all.nlp.words.model.AbstractWord
isModifiedByUserOrSystem() - Method in class org.predict4all.nlp.words.model.SimpleWord
isModifiedByUserOrSystem() - Method in interface org.predict4all.nlp.words.model.Word
isNextWordsCapitalized(List<Token>, String, int) - Method in class org.predict4all.nlp.words.WordPrefixDetector
isNGramTag() - Method in class org.predict4all.nlp.words.model.AbstractWord
isNGramTag() - Method in class org.predict4all.nlp.words.model.TagWord
isNGramTag() - Method in interface org.predict4all.nlp.words.model.Word
isNotBlank(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
isNotEmpty(Collection<?>) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
isOptional() - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher
isPredictionInitialized() - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
isSentenceSeparator() - Method in enum org.predict4all.nlp.Separator
isSeparator() - Method in class org.predict4all.nlp.parser.token.SeparatorToken
isSeparator() - Method in interface org.predict4all.nlp.parser.token.Token
isSpaceBetween() - Method in class org.predict4all.nlp.prediction.model.DoublePredictionToCompute
isTag() - Method in class org.predict4all.nlp.parser.token.TagToken
isTag() - Method in interface org.predict4all.nlp.parser.token.Token
isTokenValidToCreateUserWord(Token) - Method in class org.predict4all.nlp.words.WordDictionary
isUnique() - Method in class org.predict4all.nlp.words.NextWord
isUserWord() - Method in class org.predict4all.nlp.words.model.AbstractWord
isUserWord() - Method in class org.predict4all.nlp.words.model.UserWord
isUserWord() - Method in interface org.predict4all.nlp.words.model.Word
isValidForSaving() - Method in class org.predict4all.nlp.words.model.AbstractWord
isValidForSaving() - Method in class org.predict4all.nlp.words.model.EquivalenceClassWord
isValidForSaving() - Method in class org.predict4all.nlp.words.model.TagWord
isValidForSaving() - Method in interface org.predict4all.nlp.words.model.Word
isValidToBePredicted(PredictionParameter) - Method in class org.predict4all.nlp.words.model.AbstractWord
isValidToBePredicted(PredictionParameter) - Method in class org.predict4all.nlp.words.model.EquivalenceClassWord
isValidToBePredicted(PredictionParameter) - Method in class org.predict4all.nlp.words.model.SimpleWord
isValidToBePredicted(PredictionParameter) - Method in class org.predict4all.nlp.words.model.TagWord
isValidToBePredicted(PredictionParameter) - Method in class org.predict4all.nlp.words.model.UserWord
isValidToBePredicted(PredictionParameter) - Method in interface org.predict4all.nlp.words.model.Word: To check if this word can be displayed as a prediction result.
This typically return true for original words, but can be sensible to computation for user words.
This can also return true/false regarding Word.isForceInvalid() or Word.isForceValid() Also, user word are valid for prediction regarding PredictionParameter.getMinUseCountToValidateNewWord()
isWord() - Method in class org.predict4all.nlp.parser.token.EquivalenceClassToken
isWord() - Method in interface org.predict4all.nlp.parser.token.Token
isWord() - Method in class org.predict4all.nlp.parser.token.WordToken

K

keys() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
keys(int[]) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap

L

LanguageModel - Interface in org.predict4all.nlp.language: Represent a model specific to the input language.
This model is useful to better perform on NLP task by using specific parameters from a language.
E.G.
launchLSATraining(TrainingStep) - Method in class org.predict4all.nlp.trainer.DataTrainer
launchNGramTraining(TrainingStep) - Method in class org.predict4all.nlp.trainer.DataTrainer
LBRACKET - org.predict4all.nlp.Separator
LEAF - org.predict4all.nlp.words.correction.CorrectionRuleNodeType
length(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
listNextWords(int[], WordDictionary, PredictionParameter, Set<Integer>, Map<BiIntegerKey, NextWord>, int, boolean) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Will go through each ngram dictionary order to find the next possible words for a given prefix
Will first go through the highest order for the given prefix (e.g. prefix length == 3 = order is 4), and if the wantedCount is not reached, will go to the lower order to find new next possible.
listTrieLeaves(int[], int, int, int, BiConsumer<int[], Integer>) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Detect each unique trie leaves for a wanted order, and then call the found callback with the found prefix and word id
load(File) - Static method in class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary: Create and open a existing dynamic ngram dictionary.
loadDictionary(File, SemanticDictionaryConfiguration) - Static method in class org.predict4all.nlp.semantic.SemanticDictionary
loadDictionary(LanguageModel, File) - Static method in class org.predict4all.nlp.words.WordDictionary: Create a word dictionary from a word dictionary data file previously created with the training algorithm.
This method should not be called on user dictionary file, use WordDictionary.loadUserDictionary(File) instead.
loadFrom(File, File) - Static method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
loadFrom(LanguageModel, File) - Static method in class org.predict4all.nlp.prediction.PredictionParameter: Load prediction parameters from a JSON config file (see PredictionParameter.saveTo(File)).
loadUserDictionary(File) - Method in class org.predict4all.nlp.words.WordDictionary: To load user dictionary on an existing trained dictionary.
This will supplement this dictionary with custom word from user, or existing word with modified parameters.
This should be called on dictionary previously saved with WordDictionary.saveUserDictionary(File)
LoggingProgressIndicator - Class in org.predict4all.nlp.utils.progressindicator
LoggingProgressIndicator(String, long) - Constructor for class org.predict4all.nlp.utils.progressindicator.LoggingProgressIndicator
lowerCase(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils

M

M_FRONT_MBP - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.ApostropheMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.DateDayMonthMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.DateFullDigitMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.DateFullTextMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.DateMonthYearMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.DateWeekDayMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.NumberDecimalMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.NumberIntMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.PercentMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.ProperNameMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.language.french.matcher.SpecialWordMatcher
match(Token, TokenProvider) - Method in class org.predict4all.nlp.parser.matcher.AbstractRecursiveMatcher
match(Token, TokenProvider) - Method in interface org.predict4all.nlp.parser.matcher.TokenMatcher
MATCHERS_NGRAM_FR - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageModel
MATCHERS_SEMANTIC_ANALYSIS_FR - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageModel
matchRegexPattern(Token, TokenRegexMatcher, TokenProvider, int) - Static method in class org.predict4all.nlp.parser.matcher.TermMatcherUtils
maxOrder - Variable in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Max order possible to store in this dictionary.
Could be retrieved by opening the dictionary, or set by user as a limit.
MISC - org.predict4all.nlp.EquivalenceClass
modifiedBySystem - Variable in class org.predict4all.nlp.words.model.SimpleWord
modifiedByUser - Variable in class org.predict4all.nlp.words.model.SimpleWord
MONEY_AMOUNT - org.predict4all.nlp.EquivalenceClass
MONTHS - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageUtils

N

NEWLINE - org.predict4all.nlp.Separator
newThread(Runnable) - Method in class org.predict4all.nlp.utils.DaemonThreadFactory
next() - Method in interface org.predict4all.nlp.parser.StringProducer
NextWord - Class in org.predict4all.nlp.words
NGRAM_COUNT_FORMAT - Static variable in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
NGRAM_DICTIONARY - org.predict4all.nlp.trainer.step.TrainingStep
NGramDebugger - Interface in org.predict4all.nlp.ngram.debug: This interface can be used to check an ngram dictionary while training models.
NGramDictionaryGenerator - Class in org.predict4all.nlp.ngram: Use this generator to train an ngram model.
It will load texts from a TrainingCorpus and generate a ngram file that could be later opened with a StaticNGramTrieDictionary
NGramDictionaryGenerator(LanguageModel, TrainingConfiguration, WordDictionary) - Constructor for class org.predict4all.nlp.ngram.NGramDictionaryGenerator
NGramKey - Class in org.predict4all.nlp.ngram
NGramPruningMethod - Enum in org.predict4all.nlp.trainer.configuration
NGramTrainingDocument - Class in org.predict4all.nlp.trainer.step
NGramTrainingDocument(File, File) - Constructor for class org.predict4all.nlp.trainer.step.NGramTrainingDocument
NGramWordPredictorUtils - Class in org.predict4all.nlp.ngram: Utils class useful when predicting words with an ngram dictionaries.
NGramWordPredictorUtils(WordDictionary, PredictionParameter) - Constructor for class org.predict4all.nlp.ngram.NGramWordPredictorUtils
NODE - org.predict4all.nlp.words.correction.CorrectionRuleNodeType
NONE - org.predict4all.nlp.trainer.configuration.NGramPruningMethod
NoOpProgressIndicator - Class in org.predict4all.nlp.utils.progressindicator
NoOpProgressIndicator() - Constructor for class org.predict4all.nlp.utils.progressindicator.NoOpProgressIndicator
normalizeRow(double[]) - Static method in class org.predict4all.nlp.semantic.SemanticDictionary
NumberDecimalMatcher - Class in org.predict4all.nlp.language.french.matcher
NumberDecimalMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.NumberDecimalMatcher
NumberIntMatcher - Class in org.predict4all.nlp.language.french.matcher
NumberIntMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.NumberIntMatcher

O

of(int) - Static method in class org.predict4all.nlp.utils.BiIntegerKey
of(int, int) - Static method in class org.predict4all.nlp.utils.BiIntegerKey
of(K, T) - Static method in class org.predict4all.nlp.utils.Pair
of(K, T, V) - Static method in class org.predict4all.nlp.utils.Triple
oneInstanceCount - Static variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
open(File) - Static method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary: Create a static ngram dictionary from a given file.
OPEN_HOOK - org.predict4all.nlp.Separator
openDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Open a dictionary from a file.
To use the dictionary, the same WordDictionary used to save it should be used.
openDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.DynamicNGramDictionary
openDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
openDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
opposite() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
optional(String) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
optional(Separator) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
or(String...) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
or(Separator...) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
or(Separator, String) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
ORDER_COUNT - org.predict4all.nlp.trainer.configuration.NGramPruningMethod
org.predict4all.nlp - package org.predict4all.nlp
org.predict4all.nlp.exception - package org.predict4all.nlp.exception
org.predict4all.nlp.io - package org.predict4all.nlp.io: Contains custom InputStream and OutputStream to save/load Predict4All specific items (Token and Word).
Note that NGram are saved without these stream as they are designed to be loaded on demand with a FileChannel.
Both token and word streams extends DataOutputStream or DataInputStream : this was done for optimization, this method is much more optimized that using any other serialization methods.
org.predict4all.nlp.language - package org.predict4all.nlp.language: Represent every language specific items.
A base AbstractLanguageModel allow simpler LanguageModel implementations.
Sub-packages as "french" may contains language specific code.
org.predict4all.nlp.language.french - package org.predict4all.nlp.language.french
org.predict4all.nlp.language.french.matcher - package org.predict4all.nlp.language.french.matcher
org.predict4all.nlp.ngram - package org.predict4all.nlp.ngram: Package containing everything about the NGram model used in Predict4All.
Contains the ngram training algorithm in NGramDictionaryGenerator
Also contains AbstractNGramTrieNode : a trie structure that can be implemented in both ways : dynamic or static.
This trie structure allow having a huge number of ngram available for probability computation without loading them into memory.
org.predict4all.nlp.ngram.debug - package org.predict4all.nlp.ngram.debug
org.predict4all.nlp.ngram.dictionary - package org.predict4all.nlp.ngram.dictionary
org.predict4all.nlp.ngram.trie - package org.predict4all.nlp.ngram.trie
org.predict4all.nlp.ngram.trie.map - package org.predict4all.nlp.ngram.trie.map
org.predict4all.nlp.parser - package org.predict4all.nlp.parser: Package mainly focus on classes to convert a raw input text (as String) to Token that can be used by Predict4All.
This package is used by both training algorithms and predictor : this allow consistency among parsing and using user input.
Both word and token stream
org.predict4all.nlp.parser.matcher - package org.predict4all.nlp.parser.matcher
org.predict4all.nlp.parser.token - package org.predict4all.nlp.parser.token
org.predict4all.nlp.prediction - package org.predict4all.nlp.prediction: Main PREDICT4ALL entry point : this package contains "the glue" between every prediction components.
PREDICT4ALL core features are located in WordPredictor
org.predict4all.nlp.prediction.model - package org.predict4all.nlp.prediction.model
org.predict4all.nlp.semantic - package org.predict4all.nlp.semantic: Semantic related prediction model (WIP) - not used by current WordPredictor
org.predict4all.nlp.trainer - package org.predict4all.nlp.trainer: Represents the whole data training process managed by the main DataTrainer.
Training is done with different steps : Tokenizer TokenConverter WordDictionaryGenerator NGramDictionaryGenerator Note that the DataTrainer use TrainingCorpus and AbstractTrainingDocument : this abstraction level is useful to be able to train the model on same corpus without having to go through every training step : really useful when developing new training algorithms.
org.predict4all.nlp.trainer.configuration - package org.predict4all.nlp.trainer.configuration
org.predict4all.nlp.trainer.corpus - package org.predict4all.nlp.trainer.corpus
org.predict4all.nlp.trainer.step - package org.predict4all.nlp.trainer.step
org.predict4all.nlp.utils - package org.predict4all.nlp.utils: Contains some simple data structure and lambda interfaces and classic "utils" static classes.
org.predict4all.nlp.utils.progressindicator - package org.predict4all.nlp.utils.progressindicator
org.predict4all.nlp.words - package org.predict4all.nlp.words: Contains classes related to Word and WordDictionary
Mainly used to identify Word as unique instance identified with int ID.
This package mainly focus on managing vocabulary.
org.predict4all.nlp.words.correction - package org.predict4all.nlp.words.correction: Contains every classes and algorithms related to word correction.
The main component is WordCorrectionGenerator as it contains most of the correction logic.
CorrectionRule is also important as it the main entry point to configure word correction.
org.predict4all.nlp.words.model - package org.predict4all.nlp.words.model
OTHER - org.predict4all.nlp.Separator
OUTPUT_EXTENSION - Static variable in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
outputFile - Variable in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument

P

Pair<K,T> - Class in org.predict4all.nlp.utils
PARSER - org.predict4all.nlp.trainer.step.TrainingStep
ParserTrainingDocument - Class in org.predict4all.nlp.trainer.step
ParserTrainingDocument(String, File, File) - Constructor for class org.predict4all.nlp.trainer.step.ParserTrainingDocument
PatternMatched - Class in org.predict4all.nlp.parser.matcher
PatternMatched(String, Token) - Constructor for class org.predict4all.nlp.parser.matcher.PatternMatched
PatternMatched(EquivalenceClass, String, Token) - Constructor for class org.predict4all.nlp.parser.matcher.PatternMatched
PERCENT - org.predict4all.nlp.EquivalenceClass
PERCENT - org.predict4all.nlp.Separator
PERCENT_FORMAT - Static variable in class org.predict4all.nlp.trainer.DataTrainer
PERCENT_FORMAT - Static variable in class org.predict4all.nlp.words.WordDictionaryGenerator
PercentMatcher - Class in org.predict4all.nlp.language.french.matcher
PercentMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.PercentMatcher
PHONEM_CONFUSION_SET - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
PIPE - org.predict4all.nlp.Separator
POINT - org.predict4all.nlp.Separator
postInsertHook(boolean) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: After an insert, this hook is called to adjust the size/free values of the set and to perform rehashing if necessary.
predict(String) - Method in class org.predict4all.nlp.prediction.WordPredictor: See WordPredictor.predict(String, String, int, Set) called with default wanted size (5)
predict(String, int) - Method in class org.predict4all.nlp.prediction.WordPredictor: See WordPredictor.predict(String, String, int, Set)
predict(String, String, int) - Method in class org.predict4all.nlp.prediction.WordPredictor: See WordPredictor.predict(String, String, int, Set)
predict(String, String, int, Set<Integer>) - Method in class org.predict4all.nlp.prediction.WordPredictor: Try to predict the best wantedCount words for a given textBeforeCaret.
Will go through ngram dictionary (and eventually through dynamic dictionary) to find the best matching word.
This may predict next word if the predictor detect that there is no current word (e.g. the given textBeforeCaret ends with a space) or it may also try to complete the current word end.
If a word is already started and PredictionParameter.isEnableWordCorrection(), the given WordPrediction could be correction of the already started word.
textAfterCaret is not useful to predict next words, but it used to determine WordPredictionResult.getNextCharCountToRemove()
wantedCount should be given according to real needs : prediction computing will be longer if wantedCount it too high.
wordIdsToExclude can be useful to exclude already seen words if the current word is the same from the last prediction call.
predict(String, Set<Integer>) - Method in class org.predict4all.nlp.prediction.WordPredictor: See WordPredictor.predict(String, String, int, Set) called with default wanted size (5)
Predict4AllInfo - Class in org.predict4all.nlp: This retrieves information about the library (version and build date).
This should mostly be used to ensure consistency on saved data (i.e. save and load data from same versions)
Predict4AllInfo() - Constructor for class org.predict4all.nlp.Predict4AllInfo
Predict4AllUtils - Class in org.predict4all.nlp.utils: Contains different utils methods that are used in NLP taks.
prediction - Variable in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
PredictionParameter - Class in org.predict4all.nlp.prediction: Contains parameters to configure how WordPredictor is working.
Changes to an instance of PredictionParameter while the predictor is running could be not reflected as some values are cached internally.
PredictionParameter(LanguageModel) - Constructor for class org.predict4all.nlp.prediction.PredictionParameter
probFactor - Variable in class org.predict4all.nlp.words.model.SimpleWord
progressIndicator - Variable in class org.predict4all.nlp.trainer.TrainerTask
ProgressIndicator - Interface in org.predict4all.nlp.utils.progressindicator
PROPER_NAME - org.predict4all.nlp.EquivalenceClass
ProperNameMatcher - Class in org.predict4all.nlp.language.french.matcher
ProperNameMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.ProperNameMatcher
pruneNGramsCount(int, TrainingConfiguration) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
pruneNGramsOrderCount(int[], TrainingConfiguration) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
pruneNGramsWeightedDifference(double, TrainingConfiguration, NGramPruningMethod) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary: Execute a pruning on the dictionary.
Pruning is implemented with a "weighted difference" algorithm : difference is computed between high order model and a lower order model (e.g. difference between 4-gram - 3gram, then 3-gram - 2-gram) and if the difference is bellow a certain level (threshold), the high order model is deleted.
Difference pruning is executed for max order to bigram level, probabilities are computed again after the pruning.
pruningCountingNGram(int, int, int) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode
put(int, V) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
putAll(Map<? extends Integer, ? extends V>) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
putAndIncrementBy(int[], int) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Add a given ngram to the dictionary and to increment its count.
If the ngram is already in the dictionary, will just increment its count.
This will call AbstractNGramDictionary.putAndIncrementBy(int[], int, int) with a index = 0
putAndIncrementBy(int[], int) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
putAndIncrementBy(int[], int) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
putAndIncrementBy(int[], int, int) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Add a given ngram to the dictionary and to increment its count.
If the ngram is already in the dictionary, will just increment its count.
putAndIncrementBy(int[], int, int) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
putAndIncrementBy(int[], int, int) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
putAndIncrementBy(int[], int, int) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Put a ngram into this trie structure, create node if needed, and increment the existing one.
putIfAbsent(int, V) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
putUserWord(String) - Method in class org.predict4all.nlp.words.WordDictionary: To manually add an user word to this dictionary.
This will create the associated word entity.
This doesn't check that a previous word was in the dictionary with the same word : you should check it before calling this method (use WordDictionary.getWord(String))
putUserWord(Token) - Method in class org.predict4all.nlp.words.WordDictionary
putWordTraining(String) - Method in class org.predict4all.nlp.words.WordDictionary

Q

QUESTION - org.predict4all.nlp.Separator
QUOTE - org.predict4all.nlp.Separator

R

RAW_COUNT - org.predict4all.nlp.trainer.configuration.NGramPruningMethod
RBRACKET - org.predict4all.nlp.Separator
readAllChildren(FileChannel, int) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Read all children from a given file channel, then load recursively all the children.
readDictionaryInformation(ByteBuffer) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Read the general information for this dictionary from a given buffer (doesn't do any check)
readNodeInformation(ByteBuffer) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Read this node information from a given buffer.
readNodeInformation(ByteBuffer) - Method in class org.predict4all.nlp.ngram.trie.StaticNGramTrieNode: Read the node information contained into the given buffer to this node (without any check).
readToken() - Method in class org.predict4all.nlp.io.TokenFileInputStream
readWord() - Method in class org.predict4all.nlp.io.WordFileInputStream
rehash(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
remove(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
REMOVE_LETTER - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
removeAt(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Delete the record at index.
REMOVED - Static variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: flag indicating that the value of a slot in the hashtable was deleted
retainEntries(TIntObjectProcedure<? super V>) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
rootNode - Variable in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Root node of this dictionary (this node contains as children the whole vocabulary)
ruleBuilder() - Static method in class org.predict4all.nlp.words.correction.CorrectionRule: Initialize empty correction rule builder
run() - Method in class org.predict4all.nlp.trainer.TrainerTask

S

saveDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Save this dictionary to a file.
Will save the dictionary relative with id only, this means that the same word dictionary should be loaded if this dictionary is opened later.
saveDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
saveDictionary(File) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
saveTo(File) - Method in class org.predict4all.nlp.prediction.PredictionParameter: Save this prediction parameters to a config file that could be later loaded with PredictionParameter.loadFrom(LanguageModel, File)
This implementation used JSON to save values.
saveTo(File) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
saveUserDictionary(File) - Method in class org.predict4all.nlp.words.WordDictionary: To save this dictionary modified words.
This will saved into the given file : the UserWord added to the dictionary, but also every Word that was modified (e.g. if Word.setProbFactor(double, boolean), Word.setForceInvalid(boolean, boolean) etc... was called).
This file can later be loaded with WordDictionary.loadUserDictionary(File)
SEMANTIC_DICTIONARY - org.predict4all.nlp.trainer.step.TrainingStep
SemanticDictionary - Class in org.predict4all.nlp.semantic: Represents a semantic dictionary to be used to predict next words.
WARNING : THIS IS A WIP
SemanticDictionaryConfiguration - Interface in org.predict4all.nlp.semantic
SemanticDictionaryGenerator - Class in org.predict4all.nlp.semantic: To generate a SemanticDictionary from an input corpus.
This creates a term x term matrix and then reduces it with SVD (via an optimized R script, "Rscript" should be available in path).
SemanticDictionaryGenerator(LanguageModel, WordDictionary, TrainingConfiguration) - Constructor for class org.predict4all.nlp.semantic.SemanticDictionaryGenerator
SemanticTrainingDocument - Class in org.predict4all.nlp.trainer.step
SemanticTrainingDocument(File, File) - Constructor for class org.predict4all.nlp.trainer.step.SemanticTrainingDocument
SEMICOLON - org.predict4all.nlp.Separator
Separator - Enum in org.predict4all.nlp: Represent chars between words.
This is preferred to regex pattern because separator are fully controlled.
If you add any new separator, watch the last used id
SeparatorToken - Class in org.predict4all.nlp.parser.token
SeparatorToken(Separator) - Constructor for class org.predict4all.nlp.parser.token.SeparatorToken
SEQUENCES - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
setAddNewWordsEnabled(boolean) - Method in class org.predict4all.nlp.prediction.PredictionParameter: Enable/disable that new words can be added to dictionary while using the word predictor or while training the dynamic model.
Note that added word could appears in predictions only if they appeared enough times, as suggestion by PredictionParameter.getMinUseCountToValidateNewWord()
setBaseWordDictionaryPath(String) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setConvertCaseFromDictionaryModelThreshold(double) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setCorrectionDefaultCost(double) - Method in class org.predict4all.nlp.prediction.PredictionParameter: The default cost applied to correction rule if CorrectionRule.getCost() is null.
setCorrectionDefaultFactor(double) - Method in class org.predict4all.nlp.prediction.PredictionParameter: The default factor applied to correction rule if CorrectionRule.getFactor() is null.
setCorrectionMaxCost(double) - Method in class org.predict4all.nlp.prediction.PredictionParameter: Determine how much correction will be applied to a same input.
The higher this value, the more correction will be applied.
setCorrectionRule(CorrectionRule) - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: The correction rule associated on this node.
Will be taken into account only if CorrectionRuleNode.getType() is CorrectionRuleNodeType.LEAF
setCorrectionRulesRoot(CorrectionRuleNode) - Method in class org.predict4all.nlp.prediction.PredictionParameter: The correction rules to apply if PredictionParameter.isEnableWordCorrection() is enabled.
Correction rule are organised as a tree to allow enabling/disabled a whole part of the tree.
Correction rules can be created programmatically, or FrenchDefaultCorrectionRuleGenerator can be used.
setDebugPrefix(String) - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
setDebugPrefix(String) - Method in class org.predict4all.nlp.trainer.DataTrainer
setDirectlyValidWordCountThreshold(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setDynamicModelEnabled(boolean) - Method in class org.predict4all.nlp.prediction.PredictionParameter: Enable/disable the use of dynamic model when predicting next words.
If enabled, it should always be combined with an instance of DynamicNGramDictionary given to WordPredictor.
The model can be trained via the WordPredictor.trainDynamicModel(String, boolean)
setDynamicModelMinimumWeight(double) - Method in class org.predict4all.nlp.prediction.PredictionParameter: Useful to set the minimum weight for dynamic model when interpolating both static and dynamic model.
Value should ranger between 0.0 and 0.5.
setEnabled(boolean) - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: To know if this node should be taken into account in WordCorrectionGenerator
Note that individually node can be enabled but then ignored.
setEnableDebugInformation(boolean) - Method in class org.predict4all.nlp.prediction.PredictionParameter: To enable debug information while predictor is working.
This should be enabled carefully : debug is expensive in memory and computing cost as it creates a lot of String instance.
Typically this should never be enabled when using the predictor in production.
Enabling debug will fill WordPredictionResult.getDebugInformation() and WordPrediction.getDebugInformation()
setEnableWordCorrection(boolean) - Method in class org.predict4all.nlp.prediction.PredictionParameter: To enable/disable word correction.
Enabling this parameter will use PredictionParameter.getCorrectionRulesRoot() to determine the rules to be used by the correction algorithms.
setForceInvalid(boolean, boolean) - Method in class org.predict4all.nlp.words.model.AbstractWord
setForceInvalid(boolean, boolean) - Method in class org.predict4all.nlp.words.model.SimpleWord
setForceInvalid(boolean, boolean) - Method in interface org.predict4all.nlp.words.model.Word: To force that this word is invalid.
In fact, this method allow removal of a word from prediction result : words can't be removed from dictionary as they can be used in ngrams, but having forceInvalid true has the same effect than removing a word.
setForceValid(boolean, boolean) - Method in class org.predict4all.nlp.words.model.AbstractWord
setForceValid(boolean, boolean) - Method in class org.predict4all.nlp.words.model.SimpleWord
setForceValid(boolean, boolean) - Method in interface org.predict4all.nlp.words.model.Word: To force that this word become valid, mostly use on UserWord to ignore validation.
setLanguageModel(LanguageModel) - Method in class org.predict4all.nlp.prediction.PredictionParameter: The language model to be used to predict words.
Typically implementations are provided by the framework (see FrenchLanguageModel)
It should always be filled
setLsaDensitySize(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setLsaFrequentWordSize(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setLsaTargetSvdSize(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setLsaVocabularySize(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setLsaWindowSize(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setMinCountToProvideCorrection(int) - Method in class org.predict4all.nlp.prediction.PredictionParameter: A minimum count of char before having correction result integrated.
Note that this has not effect if PredictionParameter.isEnableWordCorrection() is disabled.
Typically, setting this value to 3 will allow predictor to check for correction only once user typed 3 chars.
setMinCountToProvidePrediction(int) - Method in class org.predict4all.nlp.prediction.PredictionParameter: A minimum count of char before having prediction result.
This built-in feature allow prediction to be displayed only after a certain amount of user input.
Typically, setting this value to 1 will disable next word prediction and will only predict current typed word prediction.
setMinUseCountToValidateNewWord(int) - Method in class org.predict4all.nlp.prediction.PredictionParameter: Minimum new word use count to be displayed in the prediction.
This avoid having typing errors displayed as prediction results.
setModifiedBySystem(boolean) - Method in class org.predict4all.nlp.words.model.AbstractWord
setModifiedBySystem(boolean) - Method in interface org.predict4all.nlp.words.model.Word: To manually set modification by system flag
setModifiedByUser(boolean) - Method in class org.predict4all.nlp.words.model.AbstractWord
setModifiedByUser(boolean) - Method in class org.predict4all.nlp.words.model.SimpleWord
setModifiedByUser(boolean) - Method in interface org.predict4all.nlp.words.model.Word: To manually set modification by user flag
setName(String) - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode: The name for this node (just informative)
setNgramDebugAfterPruning(NGramDebugger) - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
setNgramDebugAfterPruning(NGramDebugger) - Method in class org.predict4all.nlp.trainer.DataTrainer
setNgramDebugBeforePruning(NGramDebugger) - Method in class org.predict4all.nlp.ngram.NGramDictionaryGenerator
setNgramDebugBeforePruning(NGramDebugger) - Method in class org.predict4all.nlp.trainer.DataTrainer
setNgramOrder(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setNgramPruningCountThreshold(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setNgramPruningOrderCountThresholds(int[]) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setNgramPruningWeightedDifferenceThreshold(double) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setProbFactor(double, boolean) - Method in class org.predict4all.nlp.words.model.AbstractWord
setProbFactor(double, boolean) - Method in class org.predict4all.nlp.words.model.SimpleWord
setProbFactor(double, boolean) - Method in interface org.predict4all.nlp.words.model.Word: This factor can be used to modify final probabilities of the predictions.
It will be applied once probabilities are computed to influence result list.
It is mainly used in a multiplication with the original probability (and then the result list is normalized).
To only rely on probabilities, the value should be 1.0
setPruningMethod(NGramPruningMethod) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setScore(double) - Method in class org.predict4all.nlp.prediction.model.AbstractPredictionToCompute
setSmoothingDiscountValue(double) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setSmoothingDiscountValueLowerBound(double) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setSmoothingDiscountValueUpperBound(double) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setStopWordDictionaryPath(String) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setTranslationProvider(FrenchDefaultCorrectionRuleGenerator.TranslationProvider) - Static method in class org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator
setUnknownWordCountThreshold(int) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
setUp(int) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: initializes the hashtable to a prime capacity which is at least initialCapacity + 1.
setUpperCaseReplacementThreshold(double) - Method in class org.predict4all.nlp.trainer.configuration.TrainingConfiguration
SimpleGeneratingCorrection - Class in org.predict4all.nlp.words.correction
SimpleGeneratingCorrection(String, boolean) - Constructor for class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
SimpleWord - Class in org.predict4all.nlp.words.model
SimpleWord(int, String) - Constructor for class org.predict4all.nlp.words.model.SimpleWord
SimpleWord(int, String, boolean, boolean, double, boolean, boolean) - Constructor for class org.predict4all.nlp.words.model.SimpleWord
SingleThreadDoubleAdder - Class in org.predict4all.nlp.utils: Similar to DoubleAdder but for a single threaded usage.
Just a simple double reference without any overhead.
SingleThreadDoubleAdder(double) - Constructor for class org.predict4all.nlp.utils.SingleThreadDoubleAdder
size() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Returns the number of distinct elements in this collection.
size() - Method in interface org.predict4all.nlp.parser.StringProducer
size() - Method in class org.predict4all.nlp.utils.FifoSet
size() - Method in class org.predict4all.nlp.words.WordDictionary: The word count stored in this dictionary.
SLASH - org.predict4all.nlp.Separator
SPACE - org.predict4all.nlp.Separator
SpecialWordMatcher - Class in org.predict4all.nlp.language.french.matcher
SpecialWordMatcher() - Constructor for class org.predict4all.nlp.language.french.matcher.SpecialWordMatcher
start() - Static method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
START - org.predict4all.nlp.Tag
STATIC_TRIE_NODE_SIZE_BYTE - Static variable in class org.predict4all.nlp.ngram.trie.AbstractNGramTrieNode: Static node byte size (3 integer, 2 double).
Integer : word id, children size, children position.
Double : frequency, backoff weight.
StaticNGramTrieDictionary - Class in org.predict4all.nlp.ngram.dictionary: Represent a static ngram dictionary where trie node are loaded "on demand" while browsing through the nodes.

This dictionary is read only and cannot be updated or saved : methods like StaticNGramTrieDictionary.updateProbabilities(double[]), StaticNGramTrieDictionary.putAndIncrementBy(int[], int) are not supported by this dictionary.
StaticNGramTrieDictionary() - Constructor for class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
StaticNGramTrieNode - Class in org.predict4all.nlp.ngram.trie: Represent a static ngram trie node : when node are used only to retrieve information and compute probabilities, but children are never updated.
This node is particular because children node are loaded on demand from a FileChannel.
This node is produced in a read only version : to create this node, DynamicNGramTrieNode and TrainingNGramDictionary should be used.
StaticNGramTrieNode() - Constructor for class org.predict4all.nlp.ngram.trie.StaticNGramTrieNode
StopWordDictionary - Interface in org.predict4all.nlp.language: A language specific dictionary : contains every stop words for a language
strEquals(String, String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
strEqualsIgnoreCase(String, String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
StringProducer - Interface in org.predict4all.nlp.parser
strSplit(String, String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
substringInCurrentPart(int, int) - Method in interface org.predict4all.nlp.words.correction.GeneratingCorrectionI
substringInCurrentPart(int, int) - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
sum() - Method in class org.predict4all.nlp.utils.SingleThreadDoubleAdder

T

TAB - org.predict4all.nlp.Separator
Tag - Enum in org.predict4all.nlp: Represent a specific value in a corpus.
Useful to tag specific part of the corpus without any semantic information.
START : represent a sentence start UNKNOWN : represent a word/expression out of vocabulary
TagToken - Class in org.predict4all.nlp.parser.token
TagWord - Class in org.predict4all.nlp.words.model
TagWord(Tag) - Constructor for class org.predict4all.nlp.words.model.TagWord
TermMatcherUtils - Class in org.predict4all.nlp.parser.matcher
testAll() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
then(String) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
then(Separator) - Method in class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
Token - Interface in org.predict4all.nlp.parser.token: Represent the lowest unit when parsing a text.
TOKEN_CONVERT - org.predict4all.nlp.trainer.step.TrainingStep
TOKEN_COUNT_FORMAT - Static variable in class org.predict4all.nlp.parser.Tokenizer
TokenAppender - Interface in org.predict4all.nlp.parser
TokenConverter - Class in org.predict4all.nlp.parser.matcher: This token converter will convert input token list to another token list, with matched TokenMatcher pattern.
TokenConverter(TokenMatcher[]) - Constructor for class org.predict4all.nlp.parser.matcher.TokenConverter
TokenConverterTrainingDocument - Class in org.predict4all.nlp.trainer.step
TokenConverterTrainingDocument(File, File) - Constructor for class org.predict4all.nlp.trainer.step.TokenConverterTrainingDocument
TokenFileInputStream - Class in org.predict4all.nlp.io
TokenFileInputStream(File) - Constructor for class org.predict4all.nlp.io.TokenFileInputStream
TokenFileOutputStream - Class in org.predict4all.nlp.io
TokenFileOutputStream(File) - Constructor for class org.predict4all.nlp.io.TokenFileOutputStream
tokenize(String) - Method in class org.predict4all.nlp.parser.Tokenizer
tokenize(TrainingCorpus) - Method in class org.predict4all.nlp.parser.Tokenizer
Tokenizer - Class in org.predict4all.nlp.parser: This takes a raw text and to create tokens from it.
Tokenizer(LanguageModel) - Constructor for class org.predict4all.nlp.parser.Tokenizer
TokenListAppender - Class in org.predict4all.nlp.parser
TokenListAppender(List<Token>) - Constructor for class org.predict4all.nlp.parser.TokenListAppender
TokenListProvider - Class in org.predict4all.nlp.parser
TokenListProvider(Collection<Token>) - Constructor for class org.predict4all.nlp.parser.TokenListProvider
TokenMatcher - Interface in org.predict4all.nlp.parser.matcher: Represent a matcher that will try to detect if a given token match a specific pattern.
If so, the PatternMatched contains the the normalized representation of the matched tokens and eventually an EquivalenceClass.
TokenProvider - Interface in org.predict4all.nlp.parser
TokenRegexMatcher - Class in org.predict4all.nlp.parser.matcher
TokenRegexMatcher.TokenRegexMatcherBuilder - Class in org.predict4all.nlp.parser.matcher
TokenRegexMatcherBuilder() - Constructor for class org.predict4all.nlp.parser.matcher.TokenRegexMatcher.TokenRegexMatcherBuilder
TokenRegexResult - Class in org.predict4all.nlp.parser.matcher
TokenRegexResult(Token, List<String>) - Constructor for class org.predict4all.nlp.parser.matcher.TokenRegexResult
toPrimitive(Integer[]) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
toString() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
toString() - Method in class org.predict4all.nlp.prediction.WordPrediction
toString() - Method in class org.predict4all.nlp.utils.Pair
toString() - Method in class org.predict4all.nlp.utils.Triple
toString() - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
toString() - Method in class org.predict4all.nlp.words.correction.CorrectionRule
toString() - Method in class org.predict4all.nlp.words.correction.CorrectionRuleNode
toString() - Method in class org.predict4all.nlp.words.correction.SimpleGeneratingCorrection
toString() - Method in class org.predict4all.nlp.words.model.AbstractWord
toString() - Method in class org.predict4all.nlp.words.model.UserWord
toString() - Method in class org.predict4all.nlp.words.NextWord
toString() - Method in class org.predict4all.nlp.words.WordPrefixDetected
trainDynamicModel(String) - Method in class org.predict4all.nlp.prediction.WordPredictor: See WordPredictor.trainDynamicModel(String, boolean) called with ignoreLastSentence to false
trainDynamicModel(String, boolean) - Method in class org.predict4all.nlp.prediction.WordPredictor: Train the current dynamic model (if present and enabled).
This allow the dynamic model to integrate the given text as validated input for next predictions.
This will also update the "seen" word (Word.getUsageCount() and add non existing word to dictionary if PredictionParameter.isAddNewWordsEnabled() is true.
Always train your dynamic model with correct input
This method doesn't save the dynamic model, it should be then saved with TrainingNGramDictionary.saveDictionary(File)
TrainerTask - Class in org.predict4all.nlp.trainer
TrainerTask(ProgressIndicator, AbstractTrainingDocument) - Constructor for class org.predict4all.nlp.trainer.TrainerTask
TrainingConfiguration - Class in org.predict4all.nlp.trainer.configuration
TrainingCorpus - Class in org.predict4all.nlp.trainer.corpus
TrainingCorpus(int, File, File, String) - Constructor for class org.predict4all.nlp.trainer.corpus.TrainingCorpus
TrainingNGramDictionary - Class in org.predict4all.nlp.ngram.dictionary: Represent a training dictionary : a ngram dictionary used while training an ngram model.
This dictionary is useful because it supports dynamic insertion and probabilities computing...
TrainingNGramDictionary(int) - Constructor for class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
TrainingNGramDictionary(DynamicNGramTrieNode, int) - Constructor for class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
TrainingStep - Enum in org.predict4all.nlp.trainer.step: Represent the possible training steps.
This allow training to be stopped and started again at a specific step : going to converted tokens, and then running WORDS_DICTIONARY multiple times.
transformValues(TObjectFunction<V, V>) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
transitive(CachedPrecomputedCorrectionRule, CachedPrecomputedCorrectionRule) - Static method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
transitivePossible(CachedPrecomputedCorrectionRule) - Method in class org.predict4all.nlp.words.correction.CachedPrecomputedCorrectionRule
translate(String, Object...) - Method in interface org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.TranslationProvider
TrieNodeMap<V> - Class in org.predict4all.nlp.ngram.trie.map: Custom implementation copied from TIntObjectHashMap but with less attribute to reduce the heap size in Trie.
Source is copied from class hierarchy (with manually merging methods): THash TPrimitiveHash TIntHash TIntObjectHashMap The implementation is modified to keep the minimum attribute count on this Map because this TrieNodeMap will be created a lot of time !
TrieNodeMap() - Constructor for class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: Creates a new THash instance with a prime capacity at or near the minimum needed to hold initialCapacity elements with load factor loadFactor without triggering a rehash.
TrieNodeMapConstant - Class in org.predict4all.nlp.ngram.trie.map
TrieNodeMapConstant() - Constructor for class org.predict4all.nlp.ngram.trie.map.TrieNodeMapConstant
trimToSize() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: This simply calls compact.
Triple<K,T,V> - Class in org.predict4all.nlp.utils
TWO_DIGIT_FORMAT_ALWAYS - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageUtils
TWO_DIGIT_FORMAT_SOMETIMES - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageUtils
TWOPOINT - org.predict4all.nlp.Separator
TYPE_EQUIVALENCE_CLASS - Static variable in interface org.predict4all.nlp.parser.token.Token
TYPE_EQUIVALENCE_CLASS - Static variable in interface org.predict4all.nlp.words.model.Word
TYPE_NGRAM_TAG - Static variable in interface org.predict4all.nlp.words.model.Word
TYPE_SEPARATOR - Static variable in interface org.predict4all.nlp.parser.token.Token
TYPE_SIMPLE - Static variable in interface org.predict4all.nlp.words.model.Word
TYPE_TAG - Static variable in interface org.predict4all.nlp.parser.token.Token
TYPE_USER_WORD - Static variable in interface org.predict4all.nlp.words.model.Word
TYPE_WORD - Static variable in interface org.predict4all.nlp.parser.token.Token

U

uncapitalize(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
UniquePredictionToCompute - Class in org.predict4all.nlp.prediction.model
UniquePredictionToCompute(int, double, boolean, StringBuilder) - Constructor for class org.predict4all.nlp.prediction.model.UniquePredictionToCompute
UNKNOWN - org.predict4all.nlp.Tag
updateProbabilities(double[]) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Update the whole probabilities in this dictionary.
Can take a while if there is a lot of nodes in the dictionary.
updateProbabilities(double[]) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
updateProbabilities(double[]) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
updateProbabilities(int[], int, double[]) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Update probabilities in this dictionary for a specific ngram prefix : this will update the probabilities of the prefix children, and update the backoff weight of the parent node.
This is much more optimized than AbstractNGramDictionary.updateProbabilities(double[])
updateProbabilities(int[], int, double[]) - Method in class org.predict4all.nlp.ngram.dictionary.StaticNGramTrieDictionary
updateProbabilities(int[], int, double[]) - Method in class org.predict4all.nlp.ngram.dictionary.TrainingNGramDictionary
upperCase(String) - Static method in class org.predict4all.nlp.utils.Predict4AllUtils
UserWord - Class in org.predict4all.nlp.words.model
UserWord(int, String) - Constructor for class org.predict4all.nlp.words.model.UserWord
UserWord(int, String, double, boolean, boolean, long, int) - Constructor for class org.predict4all.nlp.words.model.UserWord

V

valueOf(String) - Static method in enum org.predict4all.nlp.EquivalenceClass: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.predict4all.nlp.Separator: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.predict4all.nlp.Tag: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.predict4all.nlp.trainer.configuration.NGramPruningMethod: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.predict4all.nlp.trainer.step.TrainingStep: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.predict4all.nlp.words.correction.CorrectionRuleNodeType: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.predict4all.nlp.EquivalenceClass: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
values() - Static method in enum org.predict4all.nlp.Separator: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.predict4all.nlp.Tag: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.predict4all.nlp.trainer.configuration.NGramPruningMethod: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.predict4all.nlp.trainer.step.TrainingStep: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.predict4all.nlp.words.correction.CorrectionRuleNodeType: Returns an array containing the constants of this enum type, in the order they are declared.
values(V[]) - Method in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap
VERSION - Static variable in class org.predict4all.nlp.Predict4AllInfo
VISUAL_CONFUSION - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType

W

WEEK_DAYS - Static variable in class org.predict4all.nlp.language.french.FrenchLanguageUtils
WEIGHTED_DIFFERENCE_FULL_PROB - org.predict4all.nlp.trainer.configuration.NGramPruningMethod
WEIGHTED_DIFFERENCE_RAW_PROB - org.predict4all.nlp.trainer.configuration.NGramPruningMethod
withBidirectional(boolean) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Bidirectional indicate that the resulting rule will be acting in both way : errors will be replaced with replacements and replacements will be replaced with errors.
This is quite the same as CorrectionRule.withConfusionSet(String...) with a difference is that in a confusion set, errors can be replaced by errors and replacements can be replaced with replacements, which is not the case in bidirectional rules.
If you have only one error and replacement, confusion set and bidirectional will result in the same rule.
withConfusionSet(String...) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Helper method to allow having the same errors and replacements.
This is useful if you want to create a confusion set, if the user always invert two letter or group without difference.
After creating a confusion set, CorrectionRule.getErrors() and CorrectionRule.getReplacements() will be the same.
withCost(double) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: The correction cost will influence how many correction are cumulated for a same input.
Typically, correction costs are added to check that they are bellow PredictionParameter.getCorrectionMaxCost()
withError(String...) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Determine the errors for this correction rule.
Error define the part of the text that could be replaced.
For example, if error is "a", every "a" char in user input could be potnetially replaced with CorrectionRule.withReplacement(String...) Errors should not contains any word separator(space, etc...)
withFactor(double) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: The correction factor will influence how much the correction "counts" relatively to a correct word.
withMaxIndexFromEnd(int) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Max index (from word end), exclusive (e.g. maxIndexFromEnd = 2, never apply the rule on the last two char)
Useful to ignore word ends.
withMaxIndexFromStart(int) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Max index (from word start), exclusive (e.g. maxIndexFromStart = 1, only the first char)
Useful to restrain correction to the word start.
withMinIndexFromEnd(int) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Min index, from end, inclusive (inclusive from word end, e.g. if = 1, only correct the last char)
Useful to correct only the last part of a word.
withMinIndexFromStart(int) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Min index, from start, inclusive (inclusive from word start, e.g. if = 1, never correct the first char)
Useful to correct only the "middle" area of a word
withNgramCounts(Map<Integer, Pair<Integer, Integer>>) - Method in class org.predict4all.nlp.trainer.DataTrainerResult.Builder
withReplacement(String...) - Method in class org.predict4all.nlp.words.correction.CorrectionRule: Determine the replacements that could be used to correct the CorrectionRule.getErrors().
Replacement could contains at most one word separator (space, etc...) : this allow correction merged words.
word - Variable in class org.predict4all.nlp.words.model.SimpleWord
Word - Interface in org.predict4all.nlp.words.model: Represent a word stored in a WordDictionary - word are stored with a int ID to optimize memory usage.
WORD_ENDINGS - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
WORD_SPACE_APOSTROPHE - org.predict4all.nlp.language.french.FrenchDefaultCorrectionRuleGenerator.CorrectionRuleType
WordCorrectionGenerator - Class in org.predict4all.nlp.words.correction: Generate possible correction from a input text and tokens.
Correction are based on rule (CorrectionRule) and generation is done using a thread pool.
Result correction could be unique word or double word (for example, the error might be a merged word)
WordCorrectionGenerator(WordDictionary, AbstractNGramDictionary<? extends AbstractNGramTrieNode<?>>, PredictionParameter) - Constructor for class org.predict4all.nlp.words.correction.WordCorrectionGenerator
WordDictionary - Class in org.predict4all.nlp.words: Represent a word dictionary.
This dictionary identify each sequence of chars as an unique "word" and keep information for this word.
Each word are identified by a single int ID to save memory and space.
The dictionary itself is identified with an UUID to verify consistency when using user dictionary.
Note that Word added to WordDictionary cannot be removed : their ID should be consistent and they could have been used in a AbstractNGramDictionary : however, you can disable a word with Word.setForceInvalid(boolean, boolean)
WordDictionary(LanguageModel, String) - Constructor for class org.predict4all.nlp.words.WordDictionary
WordDictionaryGenerator - Class in org.predict4all.nlp.words: This will generate a word dictionary from a TrainingCorpus : this will detect different word in training corpus and try to filter out words : match lower/upper case words, filter on a BaseWordDictionary, exclude low count words, etc.
WordDictionaryGenerator(LanguageModel, TrainingConfiguration) - Constructor for class org.predict4all.nlp.words.WordDictionaryGenerator
WordDictionaryMatchingException - Exception in org.predict4all.nlp.exception: This exception is mainly thrown if an user dictionary is loaded but is was saved from a previous dictionary.
WordDictionaryMatchingException() - Constructor for exception org.predict4all.nlp.exception.WordDictionaryMatchingException
WordDictionaryTrainingDocument - Class in org.predict4all.nlp.trainer.step
WordDictionaryTrainingDocument(File, File) - Constructor for class org.predict4all.nlp.trainer.step.WordDictionaryTrainingDocument
WordFileInputStream - Class in org.predict4all.nlp.io
WordFileInputStream(File) - Constructor for class org.predict4all.nlp.io.WordFileInputStream
WordFileOutputStream - Class in org.predict4all.nlp.io
WordFileOutputStream(File) - Constructor for class org.predict4all.nlp.io.WordFileOutputStream
WordPrediction - Class in org.predict4all.nlp.prediction: Represent a predictor from WordPredictor
WordPredictionResult - Class in org.predict4all.nlp.prediction: Contains the result from WordPredictor.
WordPredictor - Class in org.predict4all.nlp.prediction: Main entry point of PREDICT4ALL API.
Instance of WordPredictor can predict next words, current word ends and even current corrections.
The predictor mainly relies on two item : ngram dictionary and word dictionary to search for word and existing sequences.
Additionally, a dynamic model can be provided to combine both static ngrams originated from an already learned generic model and a dynamic model specific to user, profil, application...
The predictor configuration is located in PredictionParameter : the instance provided on WordPredictor creation can be later modified.
WordPredictor(PredictionParameter, WordDictionary, AbstractNGramDictionary<? extends AbstractNGramTrieNode<?>>) - Constructor for class org.predict4all.nlp.prediction.WordPredictor: Create a predictor without dynamic model
WordPredictor(PredictionParameter, WordDictionary, AbstractNGramDictionary<? extends AbstractNGramTrieNode<?>>, AbstractNGramDictionary<? extends DynamicNGramTrieNode>) - Constructor for class org.predict4all.nlp.prediction.WordPredictor: Create a predictor with dynamic model
WordPrefixDetected - Class in org.predict4all.nlp.words: Contains information about a started word (found in dictionary)
WordPrefixDetected(String, int, Map<BiIntegerKey, NextWord>, boolean) - Constructor for class org.predict4all.nlp.words.WordPrefixDetected
WordPrefixDetector - Class in org.predict4all.nlp.words: Useful to detect if a existing word is started in a token list.
It's important to detect if a word is already started when predicting next word, because the prediction result should always takes care of giving prediction result that starts like the already started word.

Because word are allowed to have word separator inside (hyphen, etc...), started word detection is much more complicated that just checking if the token list ends with a token separator.
WordPrefixDetector(WordDictionary, WordCorrectionGenerator, PredictionParameter) - Constructor for class org.predict4all.nlp.words.WordPrefixDetector
WORDS_DICTIONARY - org.predict4all.nlp.trainer.step.TrainingStep
WordToken - Class in org.predict4all.nlp.parser.token
WordToken(String) - Constructor for class org.predict4all.nlp.parser.token.WordToken
writeDictionaryInfo(ByteBuffer) - Method in class org.predict4all.nlp.ngram.dictionary.AbstractNGramDictionary: Write the general information for this dictionary to a given buffer
writeInformations(int) - Method in class org.predict4all.nlp.trainer.corpus.AbstractTrainingDocument
writeLevelForDynamicUse(FileChannel, int, int, int) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Write a trie level with DynamicNGramTrieNode.writeLevel(FileChannel, int, int, int, BiConsumer) with DynamicNGramTrieNode.writeDynamicNode(FileChannel, int) as save method.
Result trie file should be read as DynamicNGramTrieNode
writeLevelForStaticUse(FileChannel, int, int, int) - Method in class org.predict4all.nlp.ngram.trie.DynamicNGramTrieNode: Write a trie level with DynamicNGramTrieNode.writeLevel(FileChannel, int, int, int, BiConsumer) with DynamicNGramTrieNode.writeStaticNode(FileChannel, int) as save method.
Result trie file should be read as StaticNGramTrieNode
writeToken(Token) - Method in class org.predict4all.nlp.io.TokenFileOutputStream
writeWord(Word) - Method in class org.predict4all.nlp.io.WordFileOutputStream

_

_free - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: the current number of free slots in the hash.
_maxSize - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: The maximum number of elements allowed without allocating more space.
_set - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: the set of ints
_size - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: the current number of occupied slots in the hash.
_states - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: flags indicating whether each position in the hash is FREE, FULL, or REMOVED
_values - Variable in class org.predict4all.nlp.ngram.trie.map.TrieNodeMap: the values of the map

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