embed

Type Members

1. class D2V extends Serializable

   

   D2V Doc2Vec (Paragraph Vector): Doc2Vec (ParagraphVectors)

   D2V Doc2Vec (Paragraph Vector): Doc2Vec (ParagraphVectors)

   Annotations

   @SerialVersionUID()

   Note

   Quoc Le, Tomas Mikolov. Distributed Representations of Sentences and Documents. In ICML, 2014.

   ,

   reference: Quoc Le and Tomas Mikolov. Distributed Representations of Sentences and Documents. In ICML, 2014.

2. class GVec extends Serializable

   

   GVec: Global Vectors for Word Representation > Glove

   GVec: Global Vectors for Word Representation > Glove

   Annotations

   @SerialVersionUID()

   Note

   Jeffrey Pennington and Richard Socher and Christopher D. Manning. Glove: Global Vectors for Word Representation. In EMNLP, 2014.

3. class W2V extends Serializable

   

   W2V

   W2V

   Word2Vec: an Implementation of Skip-Gram Model with Negative Sampling,

   Annotations

   @SerialVersionUID()

   Note

   complexity: O = E * T * Q where Q = C * (D + D * log2(V)), E=epochs, T=total-words-of-training-data, C=max-window-size, D=embedding-size, V=vocabulary-size

   ,

   reference: Tomas Mikolov, Kai Chen, Greg Corrado and Jeffrey Dean. Efficient Estimation of Word Representations in Vector Space. In NIPS, 2013.