Handy Visual Reference of Data Model Evaluation Techniques

September 12, 2019

There are many ways to evaluate one’s data models, and Data Science Central presents an extensive yet succinct reference in visual form—“Model Evaluation Techniques in One Picture.” Together, the image and links make for a useful resource. Creator Stephanie Glen writes:

“The sheer number of model evaluation techniques available to assess how good your model is can be completely overwhelming. As well as the oft-used confidence intervals, confusion matrix and cross validation, there are dozens more that you could use for specific situations, including McNemar’s test, Cochran’s Q, Multiple Hypothesis testing and many more. This one picture whittles down that list to a dozen or so of the most popular. You’ll find links to articles explaining the specific tests and procedures below the image.”

Glen may be underselling her list of links after the graphic; it would be worth navigating to her post for that alone. The visual, though, elegantly simplifies a complex topic. It is divided into these subtopics: general tests and tools; regression; classification: visual aids; and Classification: statistics and tools. Interested readers should check it out; you might just decide to bookmark it for future reference, too.

Cynthia Murrell, September 12, 2019


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