Cancer classification from gene expression based microarray data using SVM ensemble

Abstract

Ensemble classification, which is the combination of result of a set of base learner has achieved much priority in machine learning theory. It has explored enough prospective in improving the empirical performance. There are very little bit research in Support Vector Machines (SVMs) ensemble in contrast to Neural Network or Decision Tree ensemble. To bridge this gap we analyse and compare SVM ensemble (ADASVM) with K-Nearest Neighbour (KNN) and SVM classifiers. Leukemia dataset is used as benchmark to evaluate and compare the performances of ADASVM with KNN and SVM classifiers.