A New Dependency and Correlation Analysis for Features
IEEE Transactions on Knowledge and Data Engineering
Gaussian process modelling as an indicator of neonatal seizure
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
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In this paper, we discuss the problem of feature selection for the purpose of classification and propose a solution based on the concept of mutual information. In addition, we propose a new evaluation function to measure the ability of feature subsets in distinguishing between class labels. The proposed function is based on the information gain and takes into consideration how features work together. Finally,we iscuss the performance of this function compared to that of other measures which evaluate features individually.