基于支持向量机的乳腺癌诊断

Shan Gao, Hongmei Li
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引用次数: 18

摘要

传统的乳腺癌个体诊断仍存在一些问题。针对这一问题,提出了一种基于支持向量分类方法的个人信用评估模型。利用SPSS Clementine数据挖掘工具,对个人信用数据进行支持向量机聚类分析。利用不同的核函数和支持向量机参数对其进行了详细的分析。支持向量机可用于改进医生在乳腺癌诊断中的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Breast cancer diagnosis based on support vector machine
There are some problems still exist in traditional individual Breast Cancer Diagnosis. To solve the problems, an individual credit assessment model based on support vector classification method is proposed. Using SPSS Clementine data mining tool, the personal credit data is clustering analysis by Support Vector Machine. It is analyzed in detail with the different kernel functions and parameters of Support vector machine. Support vector machine could be used to improve the work of medical practitioners in the diagnosis of breast cancer.
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