Tumor Classification Using Extreme Learning Machine Ensemble
LU Hui-juan, Jinwei Zhang · Shuxue de shijian yu renshi · 2012
In this paper,an Extreme learning machine ensemble method called DS-ELME, which is based on dataset splitting is presented.The DS-ELM-E method contains the following 3 steps:First,the training is divided dataset into k subsets,then k - 1 subsets are combined as a new training dataset,so we can get k different training dataset.Second, extreme leaning machine is used to train the k different training dataset and to obtain k different classifiers.Third,the class label of the unknown data is predicted with the ensemble classifier through majority vote method.Experiments on six tumor datasets confirms that DSE -ELM can obtain higher prediction accuracy compared with ELM,Bagging and Boosting, and more stable.