2016 | OriginalPaper | Chapter

# 15. Comparing Classifiers

Published in:
Principles of Data Mining

## Abstract

This chapter considers how to compare the performance of alternative classifiers across a range of datasets. The commonly used paired t-test is described and illustrated with worked examples, leading to the use of confidence intervals when the predictive accuracies of two classifiers are found to be significantly different.

Pitfalls involved in comparing classifiers are discussed, leading to alternative ways of comparing their performance that do not rely on comparisons of predictive accuracy.