Genetic Algorithm and Ensemble Learning Aided Text Classification using Support Vector Machines

Text classification is one of the areas where machine learning algorithms are used. The size dataset and methods used for converting textual words into vectors play a major role in classifying them. This paper proposes heuristic based approach to classify documents using Genetic Algorithm aided Support Vector Machines (SVM) Ensemble Learning approach. real valued representation data done on applying Term Frequency – Inverse Document (TF-IDF) Bi-Normal Separation (BNS). However, this paper, common misclassification issue SVM overcome by introducing two that adds weightage accurate classification. first algorithm applied BNS TF-IDF along with ensemble constructs voting classifier documents. results produced justify produces good than Henceforth subsequent vector generation. Secondly, genetic OneVsRest strategy drawback multiclass multilabel show improves accuracy even very small labelled dataset, as applies process Mutation Cross over across many generations understand pattern right