HashingTF¶

class
pyspark.mllib.feature.
HashingTF
(numFeatures=1048576)[source]¶ Maps a sequence of terms to their term frequencies using the hashing trick.
New in version 1.2.0.
 Parameters:
 numFeaturesint, optional
number of features (default: 2^20)
Notes
The terms must be hashable (can not be dict/set/list…).
Examples
>>> htf = HashingTF(100) >>> doc = "a a b b c d".split(" ") >>> htf.transform(doc) SparseVector(100, {...})
Methods
indexOf
(term)Returns the index of the input term.
setBinary
(value)If True, term frequency vector will be binary such that nonzero term counts will be set to 1 (default: False)
transform
(document)Transforms the input document (list of terms) to term frequency vectors, or transform the RDD of document to RDD of term frequency vectors.
Methods Documentation