[3E2] [General Session] 8. Soft Computing

[3E2-04] Proposal a new feature evaluation measure for filter type feature subset selection with Evolutionary Algorithm

〇Atsushi Kawamura¹, Basabi Chakuraborty² (1. Iwate Prefecture University Graduate School, 2. Iwate Prefecture University)

Keywords:Feature Selection, Evolutionary Computing

Feature Selection is an important preprocessing step for pattern recognition and data mining problems. This process selects necessary features and removes redundant features. In this work, we propose a new fitness function for feature subset evaluation. The proposed new fitness function is used for feature subset selection with EC algorithms. Simulation experiments using the benchmark datasets have been done and the results are compared with popular methods.