Effective Cancer Classification based on Gene Expression Data using Multidimensional Mutual Information and ELM

摘要

In the field of microarray data research, it is quite challenging to make classification due to small sample size and the high dimension of data. Moreover, the feature selection is crucial. In this paper, we propose multidimensional mutual information (MMI) feature selection method to select the most informative features for classification. After feature selection using the proposed MMI, Extreme Learning Machine (ELM) is used as an efficient classifier. So as to evaluate the performance of the proposed methodology, a typical dataset called Leukemia is selected to carry out a case study. Simulation results demonstrate the effectiveness of the proposed method.