论文信息 - Application of SVM to Ovarian Cancer Classification Problem

Application of SVM to Ovarian Cancer Classification Problem

In this article Sequential Minimal Optimization (SMO) approach as the solution of Support Vector Machines (SVMs) algorithm is applied to the ovarian cancer data classification problem. The comparison of different SVM models is presented in order to determine the chance of 60 months survival for a woman to be treated ovarian cancer. A cross-validation procedure is used for this purpose.

Maciej Kusy

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