Mutation-based Binary Aquila optimizer for gene selection in cancer classification.

Abstract excerpt

Microarray data classification is one of the hottest issues in the field of bioinformatics due to its efficiency in diagnosing patients' ailments. But the difficulty is that microarrays possess a huge number of genes where the majority of which are redundant or irrelevant resulting in the deterioration of classification accuracy. For this issue, mutated binary Aquila Optimizer (MBAO) with a time-varying mirrored...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Algorithms
• Share to Computational Biology
• Share to Mutation