An Analysis of the Effect of Feature Selection Methods on Classification
Raj Kishor Bisht, Aadershi Mohan, Daivik Mohan · 2023
In the present paper, a comparative study for different feature selection methods like correlation, mutual information, Fisher's test etc. has been made. Six datasets have been considered and the three feature selection techniques have been applied to these datasets. Selected features from different datasets using three different feature selection methods have been analyzed and further performance of five different classification algorithms have been examined for these features. Kurskal Wallis test is applied to check whether the performance of these classification algorithms for the selected features using three different feature selection methods for different datasets is the same or not. It is found that in spite of different subsets of features extracted by three different methods, the results of different classification algorithms are identical. The present study provides an important conclusion about feature selection methods that different subsets of features may be equally important and help to extract the most important features.