COMPARATIVE PERFORMANCE EVALUATION OF EFFICIENCY FOR HIGH DIMENSIONAL CLASSIFICATION METHODS

This paper aimed to determine the efficiency of classifiers for high-dimensional classification methods. It also investigated whether an extreme minimum misclassification rate translates into robust efficiency. To ensure acceptable procedure, a benchmark evaluation threshold (BETH) was proposed as metric analyze comparative performance A simplified derived show different achieve objectives, existing probability correct (PCC) or accuracy reported in five articles used generate BETH value. Then, analysis performed between application value and well-established PCC ,derived from confusion matrix. The indicated that procedure had rate, unlike Optimal method. results revealed inclined toward unity value, two methods (BETH PCC) became extremely irrelevant. study method invariant established by using criterion but demonstrated more relevant aspects robustness compared In addition, affirmed exhibited than concluded yields