Word Vector Learner (legacy)

Options

WordVector Training Mode

Training Mode for Word Vector training:

• Word2Vec: Training without labels. Learns word vectors based on words.
• Doc2Vec: Training with labels. Learns word vectors based on labels associated with documents.

Use Basic Token Preprocessing?

Whether to do basic preprocessing of the tokens, meaning to convert them to lower case and remove punctuation.

Seed

A seed value to use for training.

Learning Rate

The learning rate that should be used for training.

Minimum Learning Rate

Minimum learning rate threshold which the learning rate should not fall below.

Batch Size

The number of words to use for each batch.

Epochs

The number of epochs to train.

Number of Training Iterations

The number of updates done for each batch.

Layer Size

The size of the output Layer. This means this will be the length of the resulting word vectors.

Minimum Word Frequency

Minimum frequency of a word to appear in the corpus to be considered for learning. Words with a lower frequency will no appear in the vocabulary contained in the Word Vector Model.

Window Size

Size of the context, meaning number of words, to consider for learning.

Column Selection

Label Column

Possible String column containing labels for Documents.

Document Column

The column containing the Document or String to train on.

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