Accuracy Improvement of Classifiers Using Genetic Algorithm

Abstract

Accuracy of any machine learning model plays a crucial role as the prediction needs to be accurate, to prevent any discrepancy. This paper is concisely providing a way, a solution, a review on the solution of how we can improve the accuracy of the classifiers so that we get approximately accurate results. The best suited way is to apply Genetic Algorithm (GA) along with the classifiers. To analyze this approach, we will use various classifiers like Decision Tree, KNN, SVM, Gradient Boosting etc. Our main aim is to analyze the results obtained by the classifiers, firstly without GA and then with GA and observe will GA was able to improve the accuracy or not.