(Fornumericalanalysis,APclusteringalgorithmisbasedonthe"informationtransfer"betweendatapoints.Unlikek-meansalgorithmork-centeralgorithm,APalgorithmdoesnotneedtodeterminethenumberofclustersbeforerunningthealgorithm.The"examples"searchedbyAPalgorithmistheactualpointsinthedatasetastherepresentativeofeachclass)-IMDN开发者社群-imdn.cn"> (Fornumericalanalysis,APclusteringalgorithmisbasedonthe"informationtransfer"betweendatapoints.Unlikek-meansalgorithmork-centeralgorithm,APalgorithmdoesnotneedtodeterminethenumberofclustersbeforerunningthealgorithm.The"examples"searchedbyAPalgorithmistheactualpointsinthedatasetastherepresentativeofeachclass) - IMDN开发者社群-imdn.cn">
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AP

于 2021-01-07 发布
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说明:  对数值进行分析,AP聚类算法是基于数据点间的"信息传递"的一种聚类算法。与k-均值算法或k中心点算法不同,AP算法不需要在运行算法之前确定聚类的个数。AP算法寻找的"examplars"即聚类中心点是数据集合中实际存在的点,作为每类的代表(For numerical analysis, AP clustering algorithm is based on the "information transfer" between data points. Unlike k-means algorithm or k-center algorithm, AP algorithm does not need to determine the number of clusters before running the algorithm. The "examples" searched by AP algorithm is the actual points in the data set as the representative of each class)

文件列表:

A2222.m, 8040 , 2021-01-05

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