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-svdd

于 2020-03-24 发布
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说明:  SVDD 是一种重要的数据描述方法, 它能够对目标数据集进行超球形描述, 并可用于异类点检测或分类. 在现实生活中目标数据集通常包含多个样本类, 且需要同时对每一个样本类进行超球形描述。(SVDD is an important data description method, which can describe the hypersphere of the target data set, and can be used for the detection or classification of heterogeneous points. In real life, the target data set usually contains multiple sample classes, and needs to describe each sample class at the same time.)

文件列表:

exp15_svdd\kernel.m, 1871 , 2013-04-01
exp15_svdd\sample_banana_200.mat, 4030 , 2013-04-06
exp15_svdd\svddSim.m, 1337 , 2013-05-10
exp15_svdd\svddTrain.m, 1701 , 2013-04-02
exp15_svdd\svdd_banana_gauss.m, 1277 , 2014-05-24
exp15_svdd\说明.txt, 18 , 2014-05-24
exp15_svdd, 0 , 2014-05-24

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