ai.libs.jaicore.ml.cache

Class ReproducibleInstances

java.lang.Object

java.util.AbstractCollection<E>

java.util.AbstractList<weka.core.Instance>

weka.core.Instances

ai.libs.jaicore.ml.cache.ReproducibleInstances

All Implemented Interfaces:

java.io.Serializable, java.lang.Iterable<weka.core.Instance>, java.util.Collection<weka.core.Instance>, java.util.List<weka.core.Instance>, weka.core.RevisionHandler

public class ReproducibleInstances
extends weka.core.Instances

New Instances class to track splits and data origin. Origin of the dataset is stored by a LoadDataSetInstruction and changed by FoldBasedSubsetInstructions saved as a list of instructions. This history of the instances can be converted to json and used to reproduce a specific set of instances.

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.core.Instances

ARFF_DATA, ARFF_RELATION, FILE_EXTENSION, m_Attributes, m_ClassIndex, m_Instances, m_Lines, m_NamesToAttributeIndices, m_RelationName, SERIALIZED_OBJ_FILE_EXTENSION

Fields inherited from class java.util.AbstractList

modCount

Constructor Summary

Constructors

Constructor and Description
ReproducibleInstances(ReproducibleInstances dataset)

Method Summary

Modifier and Type	Method and Description
static ReproducibleInstances	fromARFF(java.io.File arffFile)
static ReproducibleInstances	fromHistory(InstructionGraph history, ai.libs.jaicore.basic.sets.Pair<java.lang.String,java.lang.Integer> outputUnitOfHistory) Creates a new ReproducibleInstances object.
static ReproducibleInstances	fromOpenML(int id, java.lang.String apiKey) Creates a new ReproducibleInstances object.
InstructionGraph	getInstructions()
ai.libs.jaicore.basic.sets.Pair<java.lang.String,java.lang.Integer>	getOutputUnit()
boolean	isCacheLookup() If true signifies that performance on this data should be looked up in cache
boolean	isCacheStorage() If true signifies that performance evaluation should be stored.
ReproducibleInstances	reduceWithInstruction(java.lang.String nameOfRefinementInstruction, Instruction instruction, int outputOfRefinementInstruction) Creates a reduced version of the dataset by using an instruction with one input and one output
void	setCacheLookup(boolean cacheLookup) If true signifies that performance on this data should be looked up in cache
void	setCacheStorage(boolean cacheStorage) If set to true, signifies that performance evaluation should be stored.
void	setOutputUnitWithoutRecomputation(ai.libs.jaicore.basic.sets.Pair<java.lang.String,java.lang.Integer> outputUnit)

Methods inherited from class weka.core.Instances

add, add, allAttributeWeightsIdentical, allInstanceWeightsIdentical, attribute, attribute, attributeStats, attributeToDoubleArray, checkForAttributeType, checkForStringAttributes, checkInstance, classAttribute, classIndex, compactify, copyInstances, delete, delete, deleteAttributeAt, deleteAttributeType, deleteStringAttributes, deleteWithMissing, deleteWithMissing, deleteWithMissingClass, enumerateAttributes, enumerateInstances, equalHeaders, equalHeadersMsg, firstInstance, get, getRandomNumberGenerator, getRevision, initialize, insertAttributeAt, instance, instancesAndWeights, kthSmallestValue, kthSmallestValue, lastInstance, main, meanOrMode, meanOrMode, mergeInstances, numAttributes, numClasses, numDistinctValues, numDistinctValues, numInstances, randomize, readInstance, relationName, remove, renameAttribute, renameAttribute, renameAttributeValue, renameAttributeValue, replaceAttributeAt, resample, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, set, setAttributeWeight, setAttributeWeight, setClass, setClassIndex, setRelationName, size, sort, sort, sortBasedOnNominalAttribute, stableSort, stableSort, stratify, stratStep, stringFreeStructure, stringWithoutHeader, sumOfWeights, swap, test, testCV, toString, toSummaryString, trainCV, trainCV, variance, variance, variances

Methods inherited from class java.util.AbstractList

addAll, clear, equals, hashCode, indexOf, iterator, lastIndexOf, listIterator, listIterator, removeRange, subList

Methods inherited from class java.util.AbstractCollection

addAll, contains, containsAll, isEmpty, remove, removeAll, retainAll, toArray, toArray

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.List

addAll, contains, containsAll, isEmpty, remove, removeAll, replaceAll, retainAll, sort, spliterator, toArray, toArray

Methods inherited from interface java.util.Collection

parallelStream, removeIf, stream

Methods inherited from interface java.lang.Iterable

forEach

Constructor Detail

ReproducibleInstances

public ReproducibleInstances(ReproducibleInstances dataset)

Method Detail

fromHistory

public static ReproducibleInstances fromHistory(InstructionGraph history,
                                                ai.libs.jaicore.basic.sets.Pair<java.lang.String,java.lang.Integer> outputUnitOfHistory)
                                         throws InstructionFailedException,
                                                java.lang.InterruptedException

Creates a new ReproducibleInstances object. Data is loaded from openml.org.

Parameters:

id - The id of the openml dataset

apiKey - apikey to use

Returns:

new ReproducibleInstances object

Throws:

java.io.IOException - if something goes wrong while loading Instances from openml

java.lang.InterruptedException

InstructionFailedException

fromOpenML

public static ReproducibleInstances fromOpenML(int id,
                                               java.lang.String apiKey)
                                        throws InstructionFailedException,
                                               java.lang.InterruptedException

Creates a new ReproducibleInstances object. Data is loaded from openml.org.

Parameters:

id - The id of the openml dataset

apiKey - apikey to use

Returns:

new ReproducibleInstances object

Throws:

java.io.IOException - if something goes wrong while loading Instances from openml

java.lang.InterruptedException

InstructionFailedException

fromARFF

public static ReproducibleInstances fromARFF(java.io.File arffFile)
                                      throws InstructionFailedException,
                                             java.lang.InterruptedException

Throws:

InstructionFailedException

java.lang.InterruptedException

getInstructions

public InstructionGraph getInstructions()

Returns:

the ordered lists of instructions or null if cache is not used

getOutputUnit

public ai.libs.jaicore.basic.sets.Pair<java.lang.String,java.lang.Integer> getOutputUnit()

setOutputUnitWithoutRecomputation

public void setOutputUnitWithoutRecomputation(ai.libs.jaicore.basic.sets.Pair<java.lang.String,java.lang.Integer> outputUnit)

isCacheStorage

public boolean isCacheStorage()

If true signifies that performance evaluation should be stored.

Returns:

true if performance should be saved

setCacheStorage

public void setCacheStorage(boolean cacheStorage)

If set to true, signifies that performance evaluation should be stored.

Parameters:

cacheStorage - the cacheStorage to set

isCacheLookup

public boolean isCacheLookup()

If true signifies that performance on this data should be looked up in cache

Returns:

true if lookup should be performed

setCacheLookup

public void setCacheLookup(boolean cacheLookup)

If true signifies that performance on this data should be looked up in cache

Parameters:

cacheLookup - the cacheLookup to set

reduceWithInstruction

public ReproducibleInstances reduceWithInstruction(java.lang.String nameOfRefinementInstruction,
                                                   Instruction instruction,
                                                   int outputOfRefinementInstruction)
                                            throws java.lang.ClassNotFoundException,
                                                   InstructionFailedException,
                                                   java.lang.InterruptedException

Creates a reduced version of the dataset by using an instruction with one input and one output

Parameters:

nameOfRefinementInstruction -

instruction -

outputOfRefinementInstruction -

Returns:

Throws:

java.lang.InterruptedException

InstructionFailedException

java.lang.ClassNotFoundException