Category Archives: Categorization

Performance Metrics for Text Categorization

One of the most common and extensively studied knowledge extraction task is text categorization. Frequently customers ask how we evaluate the quality of the output of our categorization models, especially in scenarios where each document may belong to several categories.

The idea is to be able to keep track of changes in the continuous improvement cycle of models and know if those changes have been for good or bad, to commit or reject them.

This post gives answer to this question describing the metrics that we commonly adopt for model quality assessment, depending on the categorization scenario that we are facing.

 

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Recorded webinar: Solve the most wicked text categorization problems

Thank you all for your interest in our webinar “A new tool for solving wicked text categorization problems” that we delivered last June 19th, where we explained how to use our Deep Categorization customization tool to cope with text classification scenarios where traditional machine learning technologies present limitations.

During the session we covered these items:

  • Developing categorization models in the real world
  • Categorization based on pure machine learning
  • Deep Categorization API. Pre-defined models and vertical packs
  • The new Deep Categorization Customization Tool. Semantic rule language
  • Case Study: development of a categorization model
  • Deep Categorization – Text Classification. When to use one or the other
  • Agile model development process. Combination with machine learning

IMPORTANT: this article is a tutorial based on the demonstration that we delived and that includes the data to analyze and the results of the analysis.

Interested? Here you have the presentation and the recording of the webinar.

(También presentamos este webinar en español. Tenéis la grabación aquí.)
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