Package org.apache.spark.mllib.feature

Interface Summary

Interface	Description
VectorTransformer	Trait for transformation of a vector

Class Summary

Class	Description
ChiSqSelector	Creates a ChiSquared feature selector.
ChiSqSelectorModel	Chi Squared selector model.
ChiSqSelectorModel.SaveLoadV1_0$
ElementwiseProduct	Outputs the Hadamard product (i.e., the element-wise product) of each input vector with a provided "weight" vector.
HashingTF	Maps a sequence of terms to their term frequencies using the hashing trick.
IDF	Inverse document frequency (IDF).
IDF.DocumentFrequencyAggregator	Document frequency aggregator.
IDFModel	Represents an IDF model that can transform term frequency vectors.
Normalizer	Normalizes samples individually to unit L^p^ norm
PCA	A feature transformer that projects vectors to a low-dimensional space using PCA.
PCAModel	Model fitted by PCA that can project vectors to a low-dimensional space using PCA.
PCAUtil
StandardScaler	Standardizes features by removing the mean and scaling to unit std using column summary statistics on the samples in the training set.
StandardScalerModel	Represents a StandardScaler model that can transform vectors.
VocabWord	Entry in vocabulary
Word2Vec	Word2Vec creates vector representation of words in a text corpus.
Word2VecModel	Word2Vec model param: wordIndex maps each word to an index, which can retrieve the corresponding vector from wordVectors param: wordVectors array of length numWords * vectorSize, vector corresponding to the word mapped with index i can be retrieved by the slice (i * vectorSize, i * vectorSize + vectorSize)