A Feature Selection Method Based on Minimum T - norm Using Genetic Algorithm

Feature selection plays an important role in classification for several reasons, and feature evaluation is thekey issue for constructing a feature selection algorithm. Feature selection process can also reduce noise andthis way enhance the classification accuracy. In this article, feature selection method based on minimum t– norm (MTN) by genetic algorithm (FSMTN – GA) is introduced and performance of the proposed methodon published data sets from UCI was evaluated. The results show the efficiency of the method is comparedwith the conventional version. When this method genetic algorithms and fuzzy similarity measures withminimum t – norm used in CFS method can improve it.Results can be considered quite good.

Keywords:

Feature Selection , Minimum T – norm , Genetic Algorithm