CLASSIFICATION OF EXACT IDENTIFICATION OF CANCER USING EXPRESIONS OF SUPPORT VECTOR MACHINES WITH FUZZY C-MEANS CLUSTERING

Abstract

Microarray technique is used in gene for classification and identification of cancer parts. As many machine learning and data mining techniques are implemented for finding the cancer using the expression of gene but those technique were not sufficient. Microarray data have a high degree of noise. The disadvantage of existing technique is that it work out with the drawbacks such as noise. Ranking of gene method overcome the problems in proposed technique. Commonly developed Gene ranking techniques would wrongly predict the rank when large database used. Inorder  to overcome the drawbacks in  the exisiting technique the  paper proposes a technique called Score for ranking the gene .The classifier used in the proposed technique is Support Vector Machine (SVM) with  Fuzzy C-Means Algorithm. The experiment is performed on data set lymphoma and the result shows the accuracy of classification is best when compared to the older method.