A COMPARISON OF THE CLASSIFICATION ACCURACY OF PROFILE SIMILARITY MEASURES

Abstract
Thirteen profile similarity measures were compared, using generated data. Profiles were generated from sets of three standards by adding random and normally distributed error components to the profile points of the standards. The three standards within each set were vaned systematically, altering the elevation, scatter, and shape similarities between the standards. A correct classification occurred if the generated profile was most similar to the standard from which it was generated. Significant differences were found between the proportions of correct classifications for the 13 profile similarity measures under all conditions. Osgood and Suci's D and Cattell's rB were superior to or equal to all other measures under all conditions.

This publication has 13 references indexed in Scilit: