支持向量机算法用于癌症数据建模

SVM Applied to Modeling of Cancer Date

支持向量机算法(Support Vector Machine)是基于统计学习理论(SLT)发展起来的新一代机器学习方法,并被成功地应用到很多模式识别问题中。文中支持向量机分类算法用于卵巢癌病变与非卵巢癌病变质谱数据建模。对卵巢癌数据进行判别预测,预报正确率达到98%。通过与KNN、神经网络等算法的预报结果相比较,其预报能力强于KNN、神经网络算法在这个问题中的应用,为支持向量机算法可以应用于癌症疾病辅助检测提供一例证。

As a novel kind of general learning machine based on statistical learning theory （SLT）, Support Vector Machine is received much attentions in recent years , and successfully used in some topics of pattern recognition region. SVM classification algorithms were applied to the cancer data compared with KNN and ANN, the prediction accuracy reached 98%, the results showed that SVM is a better prediction method than ANN and KNN in this problem, the model might be referred as an aiding means of the diagnosis for the cancer.