Package | Description |
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org.deeplearning4j.models.word2vec.wordstore |
Modifier and Type | Method and Description |
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VocabConstructor.Builder<T> |
VocabConstructor.Builder.addSource(@NonNull SequenceIterator<T> iterator,
int minElementFrequency)
Adds SequenceIterator for vocabulary construction.
|
VocabConstructor.Builder<T> |
VocabConstructor.Builder.allowParallelTokenization(boolean reallyAllow) |
VocabConstructor.Builder<T> |
VocabConstructor.Builder.enableScavenger(boolean reallyEnable) |
VocabConstructor.Builder<T> |
VocabConstructor.Builder.fetchLabels(boolean reallyFetch)
Sets, if labels should be fetched, during vocab building
|
VocabConstructor.Builder<T> |
VocabConstructor.Builder.setEntriesLimit(int limit)
This method sets the limit to resulting vocabulary size.
|
VocabConstructor.Builder<T> |
VocabConstructor.Builder.setIndex(InvertedIndex<T> index) |
VocabConstructor.Builder<T> |
VocabConstructor.Builder.setLockFactor(boolean lockf) |
VocabConstructor.Builder<T> |
VocabConstructor.Builder.setStopWords(@NonNull Collection<String> stopWords) |
VocabConstructor.Builder<T> |
VocabConstructor.Builder.setTargetVocabCache(@NonNull VocabCache<T> cache)
After temporary internal vocabulary is built, it will be transferred to target VocabCache you pass here
|
VocabConstructor.Builder<T> |
VocabConstructor.Builder.setUnk(T unk) |
protected VocabConstructor.Builder<T> |
VocabConstructor.Builder.useAdaGrad(boolean useAdaGrad)
Defines, if adaptive gradients should be created during vocabulary mastering
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