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Breast cancer diagnosis based on support vector machine

机译:基于支持向量机的乳腺癌诊断

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摘要

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.
机译:传统个体乳腺癌诊断中仍存在一些问题。为了解决问题,提出了一种基于支持向量分类方法的个人信用评估模型。使用SPSS克莱门汀数据挖掘工具,个人信用数据是支持向量机的聚类分析。通过不同的内核功能和支持向量机的参数详细分析了它。支持向量机可用于改善医生在乳腺癌诊断中的工作。

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