A Comprehensive Fuzzy-Based Framework for Cancer Microarray Data Gene Expression Analysis

In this paper, we employ fuzzy techniques for analysing cancer microarray gene expression data. A fuzzy-based ensemble model and a comprehensive fuzzy-based framework for cancer microarray data analysis are being proposed. Our methods were tested on three benchmark microarray cancer data sets, namely Leukemia Cancer Data Set, Colon Cancer Data Set and Lymphoma Cancer Data Set. Comparing to other traditional statistical and machine learning models, the new approach can efficiently tackle several key problems in cancer microarray gene expression data analysis, including highly correlated genes, high dimensionality, highly noisy data and further explanation of the diagnosis results.