On the information hidden in a classifier distribution.

ABSTRACT: Classification tasks are a common challenge to every field of science. To correctly interpret the results provided by a classifier, we need to know the performance indices of the classifier including its sensitivity, specificity, the most appropriate cut-off value (for continuous classifiers), etc. Typically, several studies should be conducted to find all these indices. Herein, we show that they already exist, hidden in the distribution of the variable used to classify, and can readily be harvested. An educated guess about the distribution of the variable used to classify in each class would help us to decompose the frequency distribution of the variable in population into its components-the probability density function of the variable in each class. Based on the harvested parameters, we

SUBMITTER: Habibzadeh F 

PROVIDER: S-EPMC7807039 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature