Numerical evaluation of cytologic data. III. Selection of features for discrimination.

The proper selection of variables is important in assembling a profile to best describe a given group, whether of patients or cells, vis-à-vis other groups. The need often arises to determine which variables in comparable profiles best discriminate between the profiles. Three techniques for the evaluation and selection of variables on the basis of their potentiality for discrimination are discussed in this article. The Kruskal Wallis test is useful in determining if a certain feature (variable) has any statistical significance between groups. The ambiguity function after Genchi and Mori and the measure of detectability (d') are discussed as direct measurements of a feature's ability to discriminate between groups. Fully worked numerical example suitable for execution on a pocket calculator are given.