Word Embedding for Classification Word2Vec Learner node here is trained on a training set extracted from the Human AIDS vs. Mouse Cancer dataset to provide word embedding. Each Document is then represented by only three keyords, which are then embedded using the Word Vector Apply. After splitting the value collections, word emebedding is used to train a decision tree to classify articles on human AIDS vs. articles on mouse cancer.
This is a companion discussion topic for the original entry at https://kni.me/w/xZs2KWZjgRdsqqlL