A neutral zone classifier for three classes with an application to text mining

Abstract

AbstractA classifier may be limited by its conditional misclassification rates more than its overall misclassification rate. In the case that one or more of the conditional misclassification rates are high, a neutral zone may be introduced to decrease and possibly balance the misclassification rates. In this paper, a neutral zone is incorporated into a three‐class classifier with its region determined by controlling conditional misclassification rates. The neutral zone classifier is illustrated with a text mining application that classifies written comments associated with student evaluations of teaching.