A Hybrid Approach for Feature Subset Selection and Classification Algorithm

Image categorization is a crucial field of study. There are several problems that need to be solved. For feature subset selection and picture classification, a hybrid strategy combining evolutionary algorithms and a neural network technique is applied. A canonical dataset obtained from the UCI repository is Wisconsin Breast Cancer (Diagnostic-wdbc and wpbc). A neural network is used to classify the optimized feature set after the feature set has first been optimized using a genetic algorithm. The selection of feature subsets is a crucial stage in the complexity reduction process. In this stage, the feature set’s pointless features are removed. The optimized feature set provides the foundation for further categorization. Get improved outcomes on a certain data collection by utilizing a suitable feature selection strategy.