Performance analysis of feature selection method using anova for automatic wheeze detection

In this work,we show that the classification performance of a high-dimensional features data can be improved by applying feature selection method. one-way anova were utilized and to evaluate the performance measure of the feature selection method,artificial neural network (ann) was used. from the results obtained,it can be concluded that ann performance using feature that undergo feature selection method produce a better classification accuracy compared to the ann performance using feature that did not undergo feature selection method with 93.33% against 80.00% accuracy achieved. therefore can be conclude that feature selection is a process that is crucial to be done in order to produce a good performance rate. © 2015 penerbit utm press. all rights reserved.