This extension contains a Python-based node which performs Word2Vec with both skip-gram and CBOW algorithms, letting the user choose between hierarchical softmax and negative sampling as approaches to perform the actual fit. The underlying engine for the fit and for some of the pre-processing is Tensorflow.
Extension
Word2Vec with Tensorflow
Included nodes
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Copyright by simonedigregorio
Update site information
KNIME Community Extensions (Experimental), Version 5.3.0
https://update.knime.com/community-contributions/5.3
In case you can’t install the extension via drag & drop, please check that the update site is activated .