Comprehensible classification models: a position paper

  title={Comprehensible classification models: a position paper},
  author={Alex Alves Freitas},
  journal={SIGKDD Explorations},
The vast majority of the literature evaluates the performance of classification models using only the criterion of predictive accuracy. This paper reviews the case for considering also the comprehensibility (interpretability) of classification models, and discusses the interpretability of five types of classification models, namely decision trees, classification rules, decision tables, nearest neighbors and Bayesian network classifiers. We discuss both interpretability issues which are specific… CONTINUE READING
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