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Explainable Topic Extraction with Decision Trees


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Purpose

This project is a collection of a couple different experiments and utilities for topic extraction, including:

  • Comparing popular topic extraction libraries on different kinds of documents
  • A simple implementation of decision trees to explain group membership for clustered texts
  • Some additional utilites for explaining decision tree rules based on bag of word embedding features
  • Plotting utilities for derived clusters and/or their assigned topics

Datasets

Topic Extractors


Outputs

  • The results report outlining approach and findings
  • The outputs folder, which contains breakdowns of dataset topics, topic evaluations, and tests of group differences
  • Decision tree topic extraction implementation

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Experiments and utilities for text topic extraction using decision trees

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