English

A Coefficient of Determination for Probabilistic Topic Models

Information Retrieval 2019-11-27 v2 Machine Learning Machine Learning

Abstract

This research proposes a new (old) metric for evaluating goodness of fit in topic models, the coefficient of determination, or R2R^2. Within the context of topic modeling, R2R^2 has the same interpretation that it does when used in a broader class of statistical models. Reporting R2R^2 with topic models addresses two current problems in topic modeling: a lack of standard cross-contextual evaluation metrics for topic modeling and ease of communication with lay audiences. The author proposes that R2R^2 should be reported as a standard metric when constructing topic models.

Keywords

Cite

@article{arxiv.1911.11061,
  title  = {A Coefficient of Determination for Probabilistic Topic Models},
  author = {Tommy Jones},
  journal= {arXiv preprint arXiv:1911.11061},
  year   = {2019}
}
R2 v1 2026-06-23T12:26:40.878Z