public interface DataSet extends Iterable<DataSet>, Serializable
Modifier and Type | Method and Description |
---|---|
void |
addFeatureVector(INDArray toAdd) |
void |
addFeatureVector(INDArray feature,
int example) |
void |
addRow(DataSet d,
int i) |
void |
apply(Condition condition,
com.google.common.base.Function<Number,Number> function) |
List<DataSet> |
asList() |
List<DataSet> |
batchBy(int num) |
List<DataSet> |
batchByNumLabels() |
void |
binarize() |
void |
binarize(double cutoff) |
DataSet |
copy() |
List<DataSet> |
dataSetBatches(int num)
Deprecated.
prefer
batchBy(int) |
void |
divideBy(int num) |
INDArray |
exampleMaxs() |
INDArray |
exampleMeans() |
INDArray |
exampleSums() |
void |
filterAndStrip(int[] labels) |
DataSet |
filterBy(int[] labels) |
DataSet |
get(int i) |
DataSet |
get(int[] i) |
List<String> |
getColumnNames() |
INDArray |
getFeatureMatrix() |
INDArray |
getFeatures() |
INDArray |
getFeaturesMaskArray()
Input mask array: a mask array for input, where each value is in {0,1} in order to specify whether an input is
actually present or not.
|
String |
getLabelName(int idx) |
List<String> |
getLabelNames()
Deprecated.
|
List<String> |
getLabelNames(INDArray idxs) |
List<String> |
getLabelNamesList() |
INDArray |
getLabels() |
INDArray |
getLabelsMaskArray()
Labels (output) mask array: a mask array for input, where each value is in {0,1} in order to specify whether an
output is actually present or not.
|
DataSet |
getRange(int from,
int to) |
boolean |
hasMaskArrays()
Whether the labels or input (features) mask arrays are present for this DataSet
|
String |
id() |
DataSetIterator |
iterateWithMiniBatches() |
Iterator<DataSet> |
iterator() |
Map<Integer,Double> |
labelCounts() |
void |
load(File from) |
void |
load(InputStream from) |
void |
multiplyBy(double num) |
void |
normalize() |
void |
normalizeZeroMeanZeroUnitVariance()
Deprecated.
|
int |
numExamples() |
int |
numInputs() |
int |
numOutcomes() |
int |
outcome() |
DataSet |
reshape(int rows,
int cols) |
void |
roundToTheNearest(int roundTo) |
DataSet |
sample(int numSamples) |
DataSet |
sample(int numSamples,
boolean withReplacement) |
DataSet |
sample(int numSamples,
Random rng) |
DataSet |
sample(int numSamples,
Random rng,
boolean withReplacement) |
void |
save(File to) |
void |
save(OutputStream to) |
void |
scale() |
void |
scaleMinAndMax(double min,
double max) |
void |
setColumnNames(List<String> columnNames) |
void |
setFeatures(INDArray features) |
void |
setFeaturesMaskArray(INDArray inputMask) |
void |
setLabelNames(List<String> labelNames) |
void |
setLabels(INDArray labels) |
void |
setLabelsMaskArray(INDArray labelsMask) |
void |
setNewNumberOfLabels(int labels) |
void |
setOutcome(int example,
int label) |
void |
shuffle() |
List<DataSet> |
sortAndBatchByNumLabels() |
void |
sortByLabel() |
SplitTestAndTrain |
splitTestAndTrain(double percentTrain) |
SplitTestAndTrain |
splitTestAndTrain(int numHoldout) |
SplitTestAndTrain |
splitTestAndTrain(int numHoldout,
Random rnd) |
void |
squishToRange(double min,
double max) |
void |
validate() |
forEach, spliterator
DataSet getRange(int from, int to)
void load(InputStream from)
void load(File from)
void save(OutputStream to)
void save(File to)
DataSetIterator iterateWithMiniBatches()
String id()
INDArray getFeatures()
void setFeatures(INDArray features)
DataSet copy()
DataSet reshape(int rows, int cols)
void multiplyBy(double num)
void divideBy(int num)
void shuffle()
void squishToRange(double min, double max)
void scaleMinAndMax(double min, double max)
void scale()
void addFeatureVector(INDArray toAdd)
void addFeatureVector(INDArray feature, int example)
void normalize()
void binarize()
void binarize(double cutoff)
@Deprecated void normalizeZeroMeanZeroUnitVariance()
int numInputs()
void validate()
int outcome()
void setNewNumberOfLabels(int labels)
void setOutcome(int example, int label)
DataSet get(int i)
DataSet get(int[] i)
DataSet filterBy(int[] labels)
void filterAndStrip(int[] labels)
@Deprecated List<DataSet> dataSetBatches(int num)
batchBy(int)
SplitTestAndTrain splitTestAndTrain(int numHoldout, Random rnd)
SplitTestAndTrain splitTestAndTrain(int numHoldout)
INDArray getLabels()
void setLabels(INDArray labels)
INDArray getFeatureMatrix()
void sortByLabel()
void addRow(DataSet d, int i)
INDArray exampleSums()
INDArray exampleMaxs()
INDArray exampleMeans()
DataSet sample(int numSamples)
DataSet sample(int numSamples, boolean withReplacement)
void roundToTheNearest(int roundTo)
int numOutcomes()
int numExamples()
@Deprecated List<String> getLabelNames()
String getLabelName(int idx)
SplitTestAndTrain splitTestAndTrain(double percentTrain)
INDArray getFeaturesMaskArray()
void setFeaturesMaskArray(INDArray inputMask)
INDArray getLabelsMaskArray()
void setLabelsMaskArray(INDArray labelsMask)
boolean hasMaskArrays()
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