MinCAR-Classifier for classifying lung cancer gene expression dataset

Abstract

DNA microarray technology assists researchers to learn more about different diseases especially the study of the cancer diseases. Using the microarray technology, it will be possible for the researchers to further classify the types of cancer on the basis of the patterns of gene activity (gene expression) in the tumor cells. This will tremendously help the pharmaceutical community to develop more effective drugs as the treatment strategies will be targeted directly to the specific type of cancer. The classification technique is one of the important data mining techniques that is used for classifying the DNA microarray datasets. The aim of this paper is to build an accurate classifier framework called MinCAR-Classifier that mines all minimal high confident class association rules, MinCAR, from cancer microarray datasets. Based on lung cancer microarray dataset, the comparative studies show that our proposed MinCAR-Classifier framework is more accurate than other well-known classifier frameworks.