Classification of Ovarian Cancer based on Intelligent Systems with Microarray Data

This paper studies an intelligent system, including a support vector regression (SVR) and a similar analysis, for the classification of the ovarian cancer with microarray data. That is, steps in the classification include a feature selection step and a distance measure step. Firstly, the SVR is used to do the feature selection. That is, the SVR is applied to obtain the important genes of ovarian cancer for all samples of microarray data. At the same time, we can compute the frequency of the gene selection based on the results of SVR for all samples to determine the target genes of ovarian cancer. Secondly, the distance under the similar analysis between target data and test data can be determined. From the distance results, the classification of ovarian cancer can easy to determine