Natural Language Processing Tools

Natural Language Processing tools include a dictionary builder, text featurization, unsupervised text mining, and Latent Dirichlet Allocation (LDA) training and model evaluation tips. Examine the NLP use case to learn to train a model to classify documents into categories, given a training set of documents in both of the categories.

Information about NLP operators is available at Natural Language Processing Operators.

  • Using the Results of Text Featurizer
    If you clicked Yes for the Text Featurizer's Use N-gram Values as Column Names parameter, use this process to access the full result data.
  • Unsupervised Text Mining
    You can perform unsupervised text mining to analyze collections of unstructured documents using the LDA (Latent Dirichlet Allocation) operators.
  • LDA Training and Model Evaluation Tips
    When you are using the LDA Predictor and LDA Trainer, following these guidelines can produce more meaningful results.
  • NLP Use Case
    You can use NLP Use Case to train a model to classify documents into categories, given a training set of documents in both of the categories.
  • Test Corpus Parsing
    The Team Studio N-gram Dictionary Builder can parse a text corpus, create tokens, and then parse into all possible n-grams (combinations of sequential tokens).
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