F-Index

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

F

f1(Integer) - Method in class org.deeplearning4j.eval.Evaluation: Calculate f1 score for a given class
f1() - Method in class org.deeplearning4j.eval.Evaluation: TP: true positive FP: False Positive FN: False Negative F1 score: 2 * TP / (2TP + FP + FN)
f1(int) - Method in class org.deeplearning4j.eval.EvaluationBinary: Get the F1 score for the specified output
f1Score(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier: Sets the input and labels and returns a score for the prediction wrt true labels
f1Score(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier: Returns the f1 score for the given examples.
f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer: Sets the input and labels and returns a score for the prediction wrt true labels
f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer: Returns the f1 score for the given examples.
f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.LossLayer: Sets the input and labels and returns a score for the prediction wrt true labels
f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer: Returns the f1 score for the given examples.
f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer: Returns the f1 score for the given examples.
f1Score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets the input and labels and returns a score for the prediction wrt true labels
f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Sets the input and labels and returns a score for the prediction wrt true labels
fa - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
factorial(double) - Static method in class org.deeplearning4j.util.MathUtils: This will return the factorial of the given number n.
Factory<T> - Interface in org.deeplearning4j.berkeley
Factory.DefaultFactory<T> - Class in org.deeplearning4j.berkeley
FALLBACK_LANGUAGE - Static variable in class org.deeplearning4j.ui.i18n.DefaultI18N
falseAlarmRate() - Method in class org.deeplearning4j.eval.Evaluation: False Alarm Rate (FAR) reflects rate of misclassified to classified records http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1058&context=isw
falseNegativeRate(Integer) - Method in class org.deeplearning4j.eval.Evaluation: Returns the false negative rate for a given label
falseNegativeRate(Integer, double) - Method in class org.deeplearning4j.eval.Evaluation: Returns the false negative rate for a given label
falseNegativeRate() - Method in class org.deeplearning4j.eval.Evaluation: False negative rate based on guesses so far Takes into account all known classes and outputs average fnr across all of them
falseNegatives - Variable in class org.deeplearning4j.eval.Evaluation
falseNegatives() - Method in class org.deeplearning4j.eval.Evaluation: False negatives: correctly rejected
falseNegatives(int) - Method in class org.deeplearning4j.eval.EvaluationBinary: Get the false negatives count for the specified output
falsePositiveRate(Integer) - Method in class org.deeplearning4j.eval.Evaluation: Returns the false positive rate for a given label
falsePositiveRate(Integer, double) - Method in class org.deeplearning4j.eval.Evaluation: Returns the false positive rate for a given label
falsePositiveRate() - Method in class org.deeplearning4j.eval.Evaluation: False positive rate based on guesses so far Takes into account all known classes and outputs average fpr across all of them
falsePositives - Variable in class org.deeplearning4j.eval.Evaluation
falsePositives() - Method in class org.deeplearning4j.eval.Evaluation: False positive: wrong guess
falsePositives(int) - Method in class org.deeplearning4j.eval.EvaluationBinary: Get the false positives count for the specified output
fanIn - Variable in class org.deeplearning4j.nn.weights.WeightInitUtilTest
fanOut - Variable in class org.deeplearning4j.nn.weights.WeightInitUtilTest
FEATURE_MAP_FILENAME - Static variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
FeatureInfoMap - Class in com.atilika.kuromoji.buffer
FeatureInfoMap() - Constructor for class com.atilika.kuromoji.buffer.FeatureInfoMap
featureInfos - Variable in class com.atilika.kuromoji.buffer.BufferEntry
features - Variable in class com.atilika.kuromoji.buffer.BufferEntry
features(List<String>) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
featurize(MultiDataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper: During training frozen vertices/layers can be treated as "featurizing" the input The forward pass through these frozen layer/vertices can be done in advance and the dataset saved to disk to iterate quickly on the smaller unfrozen part of the model Currently does not support datasets with feature masks
featurize(DataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper: During training frozen vertices/layers can be treated as "featurizing" the input The forward pass through these frozen layer/vertices can be done in advance and the dataset saved to disk to iterate quickly on the smaller unfrozen part of the model Currently does not support datasets with feature masks
feedDataSet(DataSet) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer
feedDataSet(DataSet) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
feedDataSet(DataSet) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Train on a DataSet
feedForward(int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType: InputType for feed forward network data
feedForward(INDArray, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Conduct forward pass using a single input array.
feedForward(INDArray[], boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Conduct forward pass using an array of inputs
feedForward() - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Conduct forward pass using the stored inputs, at test time
feedForward(boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Conduct forward pass using the stored inputs
feedForward(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute activations from input to output of the output layer
feedForward(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute activations from input to output of the output layer
feedForward() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute activations from input to output of the output layer
feedForward(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute activations from input to output of the output layer
feedForward(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute the activations from the input to the output layer, given mask arrays (that may be null) The masking arrays are used in situations such an one-to-many and many-to-one rucerrent neural network (RNN) designs, as well as for supporting time series of varying lengths within the same minibatch for RNNs.
FeedForwardLayer - Class in org.deeplearning4j.nn.conf.layers: Created by jeffreytang on 7/21/15.
FeedForwardLayer(FeedForwardLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
FeedForwardLayer.Builder<T extends FeedForwardLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
feedForwardMaskArray(INDArray, MaskState, int) - Method in interface org.deeplearning4j.nn.api.Layer: Feed forward the input mask array, setting in in the layer as appropriate.
feedForwardMaskArray(INDArray, MaskState, int) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.BaseInputPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.custom.MyCustomPreprocessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.BaseLayer
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
FeedForwardToCnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: A preprocessor to allow CNN and standard feed-forward network layers to be used together.
For example, DenseLayer -> CNN
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D or 3D with shape [numExamples, inputHeight*inputWidth*numChannels]) into 4d activations (with shape [numExamples, numChannels, inputHeight, inputWidth]) suitable to feed into CNN layers.
(b) Reshapes 4d epsilons (weights*deltas) from CNN layer, with shape [numExamples, numChannels, inputHeight, inputWidth]) into 2d epsilons (with shape [numExamples, inputHeight*inputWidth*numChannels]) for use in feed forward layer Note: numChannels is equivalent to depth or featureMaps referenced in different literature
FeedForwardToCnnPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor: Reshape to a channels x rows x columns tensor
FeedForwardToCnnPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
feedForwardToLayer(int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute the activations from the input to the specified layer.
To compute activations for all layers, use feedForward(...) methods
Note: output list includes the original input.
feedForwardToLayer(int, INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute the activations from the input to the specified layer.
To compute activations for all layers, use feedForward(...) methods
Note: output list includes the original input.
feedForwardToLayer(int, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Compute the activations from the input to the specified layer, using the currently set input for the network.
To compute activations for all layers, use feedForward(...) methods
Note: output list includes the original input.
FeedForwardToRnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: A preprocessor to allow RNN and feed-forward network layers to be used together.
For example, DenseLayer -> GravesLSTM
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D with shape [miniBatchSize*timeSeriesLength,layerSize]) into 3d activations (with shape [miniBatchSize,layerSize,timeSeriesLength]) suitable to feed into RNN layers.
(b) Reshapes 3d epsilons (weights*deltas from RNN layer, with shape [miniBatchSize,layerSize,timeSeriesLength]) into 2d epsilons (with shape [miniBatchSize*timeSeriesLength,layerSize]) for use in feed forward layer
FeedForwardToRnnPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
feedForwardWithKey(JavaPairRDD<K, INDArray[]>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Feed-forward the specified data, with the given keys.
feedForwardWithKey(JavaPairRDD<K, INDArray>, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Feed-forward the specified data, with the given keys.
FeedForwardWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.multilayer.scoring: Function to feed-forward examples, and get the network output (for example, class probabilities).
FeedForwardWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.FeedForwardWithKeyFunction
feedForwardWithKeySingle(JavaPairRDD<K, INDArray>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Feed-forward the specified data, with the given keys.
feedMultiDataSet(MultiDataSet) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer
feedMultiDataSet(MultiDataSet) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
feedMultiDataSet(MultiDataSet) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Train on a MultiDataSet
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.CurvesDataFetcher: Fetches the next dataset.
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
fetch(int) - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Deprecated.

Fetches the next dataset.
fetch(int) - Method in class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher: Fetches the next dataset.
fetch(int) - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
fetcher - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
fetchLabels(boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder: Sets, if labels should be fetched, during vocab building
fetchLabels - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
fetchLabels - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraCountFunction
fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
fieldsPresentId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
fieldsPresentId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
fieldsPresentMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
fieldsPresentMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
file - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
file(File) - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage.Builder
FILE_DIR - Variable in class org.deeplearning4j.base.MnistFetcher
FileDocumentIterator - Class in org.deeplearning4j.text.documentiterator: Iterate over files
FileDocumentIterator(String) - Constructor for class org.deeplearning4j.text.documentiterator.FileDocumentIterator
FileDocumentIterator(File) - Constructor for class org.deeplearning4j.text.documentiterator.FileDocumentIterator
FileDocumentIteratorTest - Class in org.deeplearning4j.text.documentiterator: Created by fartovii on 09.11.15.
FileDocumentIteratorTest() - Constructor for class org.deeplearning4j.text.documentiterator.FileDocumentIteratorTest
fileIterator - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
FileLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator: This is simple filesystem-based LabelAware iterator.
FileLabelAwareIterator() - Constructor for class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
FileLabelAwareIterator(List<File>, LabelsSource) - Constructor for class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
FileLabelAwareIterator.Builder - Class in org.deeplearning4j.text.documentiterator
FileLabelAwareIteratorTest - Class in org.deeplearning4j.text.documentiterator: Created by raver119 on 03.01.16.
FileLabelAwareIteratorTest() - Constructor for class org.deeplearning4j.text.documentiterator.FileLabelAwareIteratorTest
FileLabeledSentenceProvider - Class in org.deeplearning4j.iterator.provider: Iterate over a set of sentences/documents, where the sentences are to be loaded (as required) from the provided files.
FileLabeledSentenceProvider(Map<String, List<File>>) - Constructor for class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
FileLabeledSentenceProvider(Map<String, List<File>>, Random) - Constructor for class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
FILENAME_AGGREGATE_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_BROADCAST_CREATE - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_BROADCAST_GET_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
FILENAME_COUNT_RDD_SIZE - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_DATASET_GET_TIME_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
FILENAME_EXPORT_RDD_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_FIT_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
FILENAME_FIT_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_GET_INITIAL_MODEL_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
FILENAME_INIT_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
FILENAME_MAP_PARTITIONS_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_PROCESS_MINIBATCH_TIME_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
FILENAME_PROCESS_PARAMS_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_REPARTITION_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_SPLIT_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
FILENAME_TOTAL_TIME_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
fileNameClean(String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Returns a "clean" version of the given filename in which spaces have been converted to dashes and all non-alphaneumeric chars are underscores.
FilenamesLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator: This LabelAwareIterator scans folder for files, and returns them as LabelledDocuments.
FilenamesLabelAwareIterator() - Constructor for class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
FilenamesLabelAwareIterator(List<File>, LabelsSource) - Constructor for class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
FilenamesLabelAwareIterator.Builder - Class in org.deeplearning4j.text.documentiterator
FilenamesLabelAwareIteratorTest - Class in org.deeplearning4j.text.documentiterator
FilenamesLabelAwareIteratorTest() - Constructor for class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIteratorTest
FileOperations - Class in org.deeplearning4j.util
FileResourceResolver - Class in com.atilika.kuromoji.util
FileResourceResolver() - Constructor for class com.atilika.kuromoji.util.FileResourceResolver
files - Variable in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
files - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
FileSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
FileSentenceIterator(SentencePreProcessor, File) - Constructor for class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator: Takes a single file or directory
FileSentenceIterator(File) - Constructor for class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
FileStatsStorage - Class in org.deeplearning4j.ui.storage: A StatsStorage implementation that stores UI data in a file for persistence.
Can be used for multiple instances, and across multiple independent runs.
FileStatsStorage(File) - Constructor for class org.deeplearning4j.ui.storage.FileStatsStorage
fillDown(String, int) - Method in class org.deeplearning4j.util.StringGrid
fillList(Iterator<? extends T>, List<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
fillList(Iterator<? extends T>) - Static method in class org.deeplearning4j.berkeley.Iterators
fillQueue() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
Filter<T> - Interface in org.deeplearning4j.berkeley: Filters are boolean cooccurrences which accept or reject items.
filter(Iterator<T>, Filter<T>) - Static method in class org.deeplearning4j.berkeley.Iterators
filterBySimilarity(double, int, int) - Method in class org.deeplearning4j.util.StringGrid
FilteredIterator(Filter<T>, Iterator<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
FilteredIterator(Filter<T>, Iterable<T>) - Constructor for class org.deeplearning4j.berkeley.Iterators.FilteredIterator
FilteredSequenceIterator<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.iterators: This implementation of SequenceIterator passes each sequence through specified vocabulary, filtering out SequenceElements that are not available in Vocabulary.
FilteredSequenceIterator(SequenceIterator<T>, VocabCache<T>) - Constructor for class org.deeplearning4j.models.sequencevectors.iterators.FilteredSequenceIterator: Creates Filtered SequenceIterator on top of another SequenceIterator and appropriate VocabCache instance
filterMinWordAddVocab(Counter<String>) - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
filterResultsBy(Predicate<String>) - Method in class org.deeplearning4j.util.reflections.DL4JSubTypesScanner
filterRowsByColumn(int, Collection<String>) - Method in class org.deeplearning4j.util.StringGrid
filterVocab(AbstractCache<T>, int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
finalize() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
finalize() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator: Deprecated.
finalMomentum - Variable in class org.deeplearning4j.plot.BarnesHutTsne
finalMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
finalMomentum - Variable in class org.deeplearning4j.plot.Tsne
finalNOut - Static variable in class org.deeplearning4j.gradientcheck.CNN1DGradientCheckTest
finalProcessor - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
find(String, String) - Static method in class org.deeplearning4j.berkeley.StringUtils: Say whether this regular expression can be found inside this String.
findCreds() - Method in class org.deeplearning4j.aws.s3.BaseS3
findHead(Tree) - Method in class org.deeplearning4j.text.corpora.treeparser.HeadWordFinder: Finds the bottom most head
findHead2(Tree) - Method in class org.deeplearning4j.text.corpora.treeparser.HeadWordFinder
findIndex(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree: Returns the cell of this element
findNext(String, char, char, int, StringBuilder) - Static method in class org.deeplearning4j.util.StringUtils: Finds the first occurrence of the separator character ignoring the escaped separators starting from the index.
findUserDictionaryMatches(String) - Method in class com.atilika.kuromoji.dict.UserDictionary: Lookup words in text
finetune() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Run SGD based on the given labels
FineTuneConfiguration - Class in org.deeplearning4j.nn.transferlearning: Created by Alex on 21/02/2017.
FineTuneConfiguration() - Constructor for class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
fineTuneConfiguration(FineTuneConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder: Fine tune configurations specified will overwrite the existing configuration if any Usage example: specify a learning rate will set specified learning rate on all layers Refer to the fineTuneConfiguration class for more details
fineTuneConfiguration(FineTuneConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder: Set parameters to selectively override existing learning parameters Usage eg.
FineTuneConfiguration.Builder - Class in org.deeplearning4j.nn.transferlearning
FingerPrintKeyer - Class in org.deeplearning4j.util: Copied from google refine: takes the key and gets rid of all punctuation, transforms to lower case and alphabetic sorts the words
FingerPrintKeyer() - Constructor for class org.deeplearning4j.util.FingerPrintKeyer
finish() - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
finish() - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
finish() - Method in class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceReader
finish() - Method in class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceWriter
finish() - Method in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceReader
finish() - Method in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceWriter
finish() - Method in interface org.deeplearning4j.models.glove.count.CoOccurenceReader
finish() - Method in interface org.deeplearning4j.models.glove.count.CoOccurrenceWriter: Implementations of this method should close everything they use, before eradication
finish() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
finish() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
finish() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex: Finishes saving data
finish() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
finish() - Method in class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
finish() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
finish() - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
finish() - Method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareListSentenceIterator: Allows for any finishing (closing of input streams or the like)
finish() - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
finish() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator: Deprecated.
finish() - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator: Allows for any finishing (closing of input streams or the like)
finish() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
finish() - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
firstChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
FirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.FirstComparator
FirstIterationFunction - Class in org.deeplearning4j.spark.models.embeddings.word2vec
FirstIterationFunction(Broadcast<Map<String, Object>>, Broadcast<double[]>, Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunction
FirstIterationFunctionAdapter - Class in org.deeplearning4j.spark.models.embeddings.word2vec
FirstIterationFunctionAdapter(Broadcast<Map<String, Object>>, Broadcast<double[]>, Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunctionAdapter
fit() - Method in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
fit() - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer: Train the model
fit(DataSet) - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
fit(MultiDataSet) - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
fit() - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
fit(DataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
fit(MultiDataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
fit(DataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
fit(MultiDataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
fit() - Method in interface org.deeplearning4j.earlystopping.trainer.IEarlyStoppingTrainer: Conduct early stopping training
fit(IGraph<V, E>, int) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk: Fit the model, in parallel.
fit(GraphWalkIteratorProvider<V>) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk: Fit the model, in parallel, using a given GraphWalkIteratorProvider.
This object is used to generate multiple GraphWalkIterators, which can then be distributed to each thread to do in parallel
Note that DeepWalk.fit(IGraph, int) will be more convenient in many cases
Note that DeepWalk.initialize(IGraph) or DeepWalk.initialize(int[]) must be called first.
fit(GraphWalkIterator<V>) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk: Fit the DeepWalk model using a single thread using a given GraphWalkIterator.
fit(EntryPointFitParameters) - Method in class org.deeplearning4j.keras.DeepLearning4jEntryPoint: Performs fitting of the model which is referenced in the parameters according to learning parameters specified.
fit() - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences
fit() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
fit() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors: Starts training over
fit(DataSetIterator) - Method in interface org.deeplearning4j.nn.api.Classifier: Train the model based on the datasetiterator
fit(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier: Fit the model
fit(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier: Fit the model
fit(INDArray, int[]) - Method in interface org.deeplearning4j.nn.api.Classifier: Fit the model
fit() - Method in interface org.deeplearning4j.nn.api.Model: All models have a fit method
fit(INDArray) - Method in interface org.deeplearning4j.nn.api.Model: Fit the model to the given data
fit(DataSet) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Fit the ComputationGraph using a DataSet.
fit(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Fit the ComputationGraph using a DataSetIterator.
fit(MultiDataSet) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Fit the ComputationGraph using a MultiDataSet
fit(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Fit the ComputationGraph using a MultiDataSetIterator
fit(INDArray[], INDArray[]) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Fit the ComputationGraph given arrays of inputs and labels.
fit(INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Fit the ComputationGraph using the specified inputs and labels (and mask arrays)
fit() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
fit(INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.ActivationLayer
fit() - Method in class org.deeplearning4j.nn.layers.BaseLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer: Fit the model
fit(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer: Fit the model
fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer: Fit the model
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer: Fit the model to the given data
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
fit() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.DropoutLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.dense.DenseLayer
fit() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.LossLayer
fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer: Fit the model
fit(DataSet) - Method in class org.deeplearning4j.nn.layers.LossLayer: Fit the model
fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.LossLayer: Fit the model
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
fit(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
fit() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
fit(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit(INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the unsupervised model
fit(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Fit the model
fit() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
fit() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
fit(MultiDataSetIterator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
fit(DataSetIterator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: This method takes DataSetIterator, and starts training over it by scheduling DataSets to different executors
fit() - Method in class org.deeplearning4j.plot.BarnesHutTsne
fit(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
fit(INDArray, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne: Deprecated.
Use BarnesHutTsne.fit(INDArray)
fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
fit() - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
fit(RDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the ComputationGraph with the given data set
fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the ComputationGraph with the given data set
fit(String) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the SparkComputationGraph network using a directory of serialized DataSet objects The assumption here is that the directory contains a number of DataSet objects, each serialized using DataSet.save(OutputStream)
fit(String, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Deprecated.
Use SparkComputationGraph.fit(String)
fit(String, int, RecordReader) - Method in class org.deeplearning4j.spark.impl.layer.SparkDl4jLayer: Fit the layer based on the specified org.deeplearning4j.spark context text file
fit(JavaSparkContext, JavaRDD<LabeledPoint>) - Method in class org.deeplearning4j.spark.impl.layer.SparkDl4jLayer: Fit the given rdd given the context.
fit(RDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Fit the DataSet RDD.
fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Fit the DataSet RDD
fit(String) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Fit the SparkDl4jMultiLayer network using a directory of serialized DataSet objects The assumption here is that the directory contains a number of DataSet objects, each serialized using DataSet.save(OutputStream)
fit(String, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Deprecated.
Use SparkDl4jMultiLayer.fit(String)
fit() - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors: Deprecated.
fit() - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec: Deprecated.
fitContinuousLabeledPoint(JavaRDD<LabeledPoint>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Fits a MultiLayerNetwork using Spark MLLib LabeledPoint instances This will convert labeled points that have continuous labels used for regression to the internal DL4J data format and train the model on that
fitDataSet(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.layer.SparkDl4jLayer: Fit a java rdd of dataset
fitFeaturized(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper: Fit from a featurized dataset.
fitFeaturized(MultiDataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
fitFeaturized(DataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
fitFeaturized(DataSetIterator) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
fitLabeledPoint(JavaRDD<LabeledPoint>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Fit a MultiLayerNetwork using Spark MLLib LabeledPoint instances.
fitLabelledDocuments(JavaRDD<LabelledDocument>) - Method in class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors: This method builds ParagraphVectors model, expecting JavaRDD.
fitLists(JavaRDD<List<T>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors: Utility method.
fitMulti(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
fitMulti(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
fitMulti(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
fitMultiDataSet(RDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the ComputationGraph with the given data set
fitMultiDataSet(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the ComputationGraph with the given data set
fitMultiDataSet(String) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the SparkComputationGraph network using a directory of serialized MultiDataSet objects The assumption here is that the directory contains a number of serialized MultiDataSet objects
fitMultiDataSet(String, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Deprecated.
use SparkComputationGraph.fitMultiDataSet(String)
fitMultipleFiles(JavaPairRDD<String, String>) - Method in class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors: This method builds ParagraphVectors model, expecting JavaPairRDD with key as label, and value as document-in-a-string.
fitPaths(JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the network using a list of paths for serialized DataSet objects.
fitPaths(JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer: Fit the network using a list of paths for serialized DataSet objects.
fitPathsMultiDataSet(JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph: Fit the network using a list of paths for serialized MultiDataSet objects.
fitSentences(JavaRDD<String>) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
fitSequences(JavaRDD<Sequence<T>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors: Base training entry point
FixedClusterCountStrategy - Class in org.deeplearning4j.clustering.algorithm.strategy
FixedClusterCountStrategy() - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
FixedClusterCountStrategy(Integer, String, boolean) - Constructor for class org.deeplearning4j.clustering.algorithm.strategy.FixedClusterCountStrategy
FixedIterationCountCondition - Class in org.deeplearning4j.clustering.algorithm.condition
FixedIterationCountCondition() - Constructor for class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
FixedIterationCountCondition(int) - Constructor for class org.deeplearning4j.clustering.algorithm.condition.FixedIterationCountCondition
FlatModelUtils<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.reader.impl: This model reader is suited for model tests, and for cases where flat scan against elements is required.
FlatModelUtils() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.FlatModelUtils
FlatModelUtilsTest - Class in org.deeplearning4j.models.embeddings.reader.impl: These are temporary tests and will be removed after issue is solved.
FlatModelUtilsTest() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.FlatModelUtilsTest
flattenedGradients - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
flattenedGradients - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
flattenedParams - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
flattenedParams - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
flatteningOrderForVariable(String) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
flatteningOrderForVariable(String) - Method in interface org.deeplearning4j.nn.gradient.Gradient: Return the gradient flattening order for the specified variable, or null if it is not explicitly set
flattenToY(ModelInfo, GraphVertex[], List<String>, int) - Method in class org.deeplearning4j.ui.flow.FlowIterationListener: Deprecated.

This method returns all Layers connected to the currentInput
flattenToY(ModelInfo, GraphVertex[], List<String>, int) - Method in class org.deeplearning4j.ui.flow.RemoteFlowIterationListener: This method returns all Layers connected to the currentInput
floatIterable(int, int) - Static method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIteratorTest
FloatsDataSetIterator - Class in org.deeplearning4j.datasets.iterator: float[] wrapper for DataSetIterator impementation.
FloatsDataSetIterator(Iterable<Pair<float[], float[]>>, int) - Constructor for class org.deeplearning4j.datasets.iterator.FloatsDataSetIterator
floatValue(StyleDiv.FloatValue) - Method in class org.deeplearning4j.ui.components.component.style.StyleDiv.Builder: CSS float styling option
FlowIterationListener - Class in org.deeplearning4j.ui.flow: Deprecated.
Use StatsListener and UIServer.attach(StatsStorage). See examples repo for how.
FlowIterationListener() - Constructor for class org.deeplearning4j.ui.flow.FlowIterationListener: Deprecated.
FlowIterationListener(int) - Constructor for class org.deeplearning4j.ui.flow.FlowIterationListener: Deprecated.

Creates IterationListener and attaches it local UIServer instance
FlowIterationListener(String, int, int) - Constructor for class org.deeplearning4j.ui.flow.FlowIterationListener: Deprecated.
FlowIterationListener(StatsStorageRouter, int, String, String, boolean) - Constructor for class org.deeplearning4j.ui.flow.FlowIterationListener: Deprecated.
FlowIterationListener(UiConnectionInfo, int) - Constructor for class org.deeplearning4j.ui.flow.FlowIterationListener: Deprecated.
FlowIterationListenerTest - Class in org.deeplearning4j.ui.flow: This set of tests addresses different stages of model state serialization for later visualization
FlowIterationListenerTest() - Constructor for class org.deeplearning4j.ui.flow.FlowIterationListenerTest
FlowListenerModule - Class in org.deeplearning4j.ui.module.flow: Module for FlowIterationListener
FlowListenerModule() - Constructor for class org.deeplearning4j.ui.module.flow.FlowListenerModule
FlowStaticPersistable - Class in org.deeplearning4j.ui.flow.data: Created by Alex on 25/10/2016.
FlowStaticPersistable() - Constructor for class org.deeplearning4j.ui.flow.data.FlowStaticPersistable
FlowUpdatePersistable - Class in org.deeplearning4j.ui.flow.data: Created by Alex on 25/10/2016.
FlowUpdatePersistable() - Constructor for class org.deeplearning4j.ui.flow.data.FlowUpdatePersistable
FoldBetweenPartitionFunction - Class in org.deeplearning4j.spark.text.functions
FoldBetweenPartitionFunction(Broadcast<Counter<Integer>>) - Constructor for class org.deeplearning4j.spark.text.functions.FoldBetweenPartitionFunction
foldersToScan - Variable in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator.Builder
foldersToScan - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator.Builder
FoldWithinPartitionFunction - Class in org.deeplearning4j.spark.text.functions
FoldWithinPartitionFunction(Accumulator<Counter<Integer>>) - Constructor for class org.deeplearning4j.spark.text.functions.FoldWithinPartitionFunction
font(String) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder: Specify the font to be used for the text
fontSize(double) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder: Size of the font (pt)
foreach(JavaDStream<K>, Function<JavaRDD<K>, Void>) - Static method in class org.deeplearning4j.streaming.pipeline.spark.StreamingContextUtils
forgetGateBiasInit(double) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder: Set forget gate bias initalizations.
forgetGateBiasInit(double) - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM.Builder: Set forget gate bias initalizations.
format(PatriciaTrie<V>) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter: Format trie
format(PatriciaTrie<V>, boolean) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter: Format trie
format(PatriciaTrie<V>, File) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter: Format trie and write to file
format(PatriciaTrie<V>, File, boolean) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter: Format trie and write to file
format(ViterbiLattice) - Method in class com.atilika.kuromoji.viterbi.ViterbiFormatter
format(ViterbiLattice, List<ViterbiNode>) - Method in class com.atilika.kuromoji.viterbi.ViterbiFormatter
formatPercent(double, int) - Static method in class org.deeplearning4j.util.StringUtils: Format a percentage for presentation to the user.
formatTime(long) - Static method in class org.deeplearning4j.util.StringUtils: Given the time in long milliseconds, returns a String in the format Xhrs, Ymins, Z sec.
formatTimeDiff(long, long) - Static method in class org.deeplearning4j.util.StringUtils: Given a finish and start time in long milliseconds, returns a String in the format Xhrs, Ymins, Z sec, for the time difference between two times.
frame - Variable in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
frame - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
frame - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDBOW
frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDM
frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in interface org.deeplearning4j.spark.models.sequencevectors.learning.SparkElementsLearningAlgorithm
from - Variable in class org.deeplearning4j.nn.conf.graph.UnstackVertex
fromBinary(JavaPairRDD<String, PortableDataStream>, RecordReader) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Convert a traditional sc.binaryFiles in to something usable for machine learning
fromBinary(JavaRDD<Tuple2<String, PortableDataStream>>, RecordReader) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Convert a traditional sc.binaryFiles in to something usable for machine learning
fromBytesSerializable(byte[]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
fromContinuousLabeledPoint(JavaSparkContext, JavaRDD<LabeledPoint>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Deprecated.
Use MLLibUtil.fromContinuousLabeledPoint(JavaRDD)
fromContinuousLabeledPoint(JavaRDD<LabeledPoint>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Converts a continuous JavaRDD LabeledPoint to a JavaRDD DataSet.
fromContinuousLabeledPoint(JavaRDD<LabeledPoint>, boolean) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Converts a continuous JavaRDD LabeledPoint to a JavaRDD DataSet.
fromDataSet(JavaSparkContext, JavaRDD<DataSet>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Deprecated.
Use MLLibUtil.fromDataSet(JavaRDD)
fromDataSet(JavaRDD<DataSet>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Convert an rdd of data set in to labeled point.
fromDataSet(JavaRDD<DataSet>, boolean) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Convert an rdd of data set in to labeled point.
fromFile(String, String) - Static method in class org.deeplearning4j.util.StringGrid
fromInput(InputStream, String) - Static method in class org.deeplearning4j.util.StringGrid
fromJson(String) - Static method in class org.deeplearning4j.models.embeddings.loader.VectorsConfiguration
fromJson(String) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
fromJson(String) - Static method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration: Create a computation graph configuration from json
fromJson(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration: Create a neural net configuration from json
fromJson(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Create a neural net configuration from json
fromJson(String) - Static method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
fromJson(String) - Static method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster: Create a ParameterAveragingTrainingMaster instance by deserializing a JSON string that has been serialized with ParameterAveragingTrainingMaster.toJson()
fromLabeledPoint(JavaRDD<LabeledPoint>, int, int) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Convert an rdd of labeled point based on the specified batch size in to data set
fromLabeledPoint(JavaSparkContext, JavaRDD<LabeledPoint>, int) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Deprecated.
Use MLLibUtil.fromLabeledPoint(JavaRDD, int)
fromLabeledPoint(JavaRDD<LabeledPoint>, int) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Converts JavaRDD labeled points to JavaRDD datasets.
fromLabeledPoint(JavaRDD<LabeledPoint>, int, boolean) - Static method in class org.deeplearning4j.spark.util.MLLibUtil: Converts JavaRDD labeled points to JavaRDD DataSets.
fromPair(Pair<InMemoryLookupTable, VocabCache>) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Load word vectors from the given pair
fromString(String, String) - Static method in class org.deeplearning4j.util.MathUtils: This will take a given string and separator and convert it to an equivalent double array.
fromTableAndVocab(WeightLookupTable, VocabCache) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Load word vectors for the given vocab and table
fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration: Create a neural net configuration from json
fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration: Create a neural net configuration from json
fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Create a neural net configuration from json
fromYaml(String) - Static method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
fromYaml(String) - Static method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster: Create a ParameterAveragingTrainingMaster instance by deserializing a YAML string that has been serialized with ParameterAveragingTrainingMaster.toYaml()
FrozenLayer<LayerT extends Layer> - Class in org.deeplearning4j.nn.layers: For purposes of transfer learning A frozen layers wraps another dl4j layer within it.
FrozenLayer(LayerT) - Constructor for class org.deeplearning4j.nn.layers.FrozenLayer
FrozenLayerTest - Class in org.deeplearning4j.nn.layers: Created by susaneraly on 2/5/17.
FrozenLayerTest() - Constructor for class org.deeplearning4j.nn.layers.FrozenLayerTest
function(Function<T, Result>) - Static method in class org.deeplearning4j.ui.play.misc.FunctionUtil
function0(Supplier<Result>) - Static method in class org.deeplearning4j.ui.play.misc.FunctionUtil
FunctionType - Enum in org.deeplearning4j.ui.api: Enumeration for the type of function.
FunctionUtil - Class in org.deeplearning4j.ui.play.misc: Utility methods for Routing
FunctionUtil() - Constructor for class org.deeplearning4j.ui.play.misc.FunctionUtil
fwdPassOutput - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
fwdPassOutputAsArrays - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
FwdPassReturn - Class in org.deeplearning4j.nn.layers.recurrent: Created by benny on 12/31/15.
FwdPassReturn() - Constructor for class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
fz - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn

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