Opposition-Based Enhanced Grey Wolf Optimization Algorithm for Feature Selection in Breast Density Classification
Rahul Hans, Harjot Kaur · International Journal of Machine Learning and Computing · 2020
Breast Cancer is the most widespread cancer amongst women in the world.An increase in the density of breast may lead to an increase in the risk of breast cancer.For the accurate diagnosis of breast cancer, these days Machine learning-based computer-aided diagnosis systems are widely used to assist the radiologists.However, there is still a scope of improvement in the computer-aided diagnosis system for the feature selection problem, which is considered as an optimization problem.Optimization techniques are the methods where the finest solution to a problem is found by using random search mechanism.Grey wolf optimization is one of the most recent optimization algorithms.This paper presents an enhanced version of Grey Wolf Optimization algorithm and tests the performance of the proposed version of the algorithm on thirteen different benchmark functions and the binary version of the proposed algorithm is used for selecting optimal number of features for breast density classification problem.