Arif Index for Predicting the Classification Accuracy of Features and Its Application in Heart Beat Classification Problem

Authors:
Muhammad Arif;Fayyaz A. Afsar;Muhammad Usman Akram;Adnan Fida
Affiliations:
Department of Electrical Engineering, Air University, Islamabad, Pakistan;Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan;Department of Computer and Information Sciences, PIEAS, Islamabad, Pakistan;Department of Electrical Engineering, COMSATS Institute of Information Technology, Pakistan
Venue:
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Year:
2009

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Abstract

In this paper, Arif Index is proposed that can be used to assess the discrimination power of features in pattern classification problems. Discrimination power of features play an important role in the classification accuracy of a particular classifier applied to the pattern classification problem. Optimizing the performance of a classifier requires a prior knowledge of maximum achievable accuracy in pattern classification using a particular set of features. Moreover, it is also desirable to know that this set of features is separable by a decision boundary of any arbitrary complexity or not. Proposed index varies linearly with the overlap of features of different classes in the feature space and hence can be used in predicting the classification accuracy of the features that can be achieved by some optimal classifier. Using synthetic data, it is shown that the predicted accuracy and Arif index are very strongly correlated with each other (R 2 = 0.99). Implementation of the index is simple and time efficient. Index was tested on Arrhythmia beat classification problem and predicted accuracy was found to be in consistent with the reported results.