Improved binary particle swarm optimization using catfish effect for feature selection

The feature selection process constitutes a commonly encountered problem of global combinatorial optimization. This process reduces the number of features by removing irrelevant, noisy, and redundant data, thus resulting in acceptable classification accuracy. Feature selection is a preprocessing technique with great importance in the fields of data analysis… CONTINUE READING



Citations per Year

168 Citations

Semantic Scholar estimates that this publication has 168 citations based on the available data.

See our FAQ for additional information.