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GBayesian_Claa\Project 1\abalone\abalone

..............\.........\.......\abalone.asv

..............\.........\.......\abalone.m

..............\.........\.......\abalone.names

..............\.........\.......\data.mat

..............\.........\.......\Description.txt

..............\.........\.......\Index.txt

..............\.........\.......\SplitMatrixRandom.m

..............\.........\breast_cancer_wisconsin\breast-cancer-wisconsin.data

..............\.........\.......................\breast-cancer-wisconsin.names

..............\.........\.......................\breast_cancer_wisconsin.asv

..............\.........\.......................\breast_cancer_wisconsin_even.asv

..............\.........\.......................\breast_cancer_wisconsin_radom.m

..............\.........\.......................\breast_cancer_wisconsin_radom_1.asv

..............\.........\.......................\data.mat

..............\.........\.......................\Description.txt

..............\.........\.......................\exercise1.asv

..............\.........\.......................\ID.mat

..............\.........\.......................\Index.txt

..............\.........\.......................\SplitMatrixRandom.asv

..............\.........\.......................\SplitMatrixRandom.m

..............\.........\.......................\unformatted-data.txt

..............\.........\.......................\wdbc.data

..............\.........\.......................\wdbc.names

..............\.........\.......................\wpbc.data

..............\.........\.......................\wpbc.names

..............\.........\exercise2.m

..............\.........\Project Assignment 1.pdf

..............\.........\Readme File arragement.txt

..............\.........\abalone

..............\.........\breast_cancer_wisconsin

..............\Project 1

GBayesian_Claa

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使用高斯模型对威斯康辛州大学医学院长期乳腺癌数据进行了贝叶叶斯模式识别。识别率为95以上,可以作为模式识别的重要案例

时间:2019-10-07    点击: 次    - 小 + 大

上一篇:使用SVM分类器来预测乳腺癌病人的预后(特征选择;分类器构建),评价模型时使用无被交叉验证,性能评价..

下一篇:乳腺癌分类程序,带有有部分的原始数据,非常好

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