nmi指数matlab代码-Clustering-by-InTree-Ensemble-PR2020:"EnhancingIn-Tree-ba

上传者: 38629391 | 上传时间: 2023-02-08 17:32:39 | 文件大小: 36.53MB | 文件类型: ZIP
nmi指数matlab代码演示快速入门 运行 demo.m。 这可以在 30 个测试数据集上为以下两种聚类方法重现图 4A 中的结果。 ND-Ward-E(KT) :2020年Pattern Recognition上发表的拟议聚类方法(标题:邱和李的“Enhancing In-Tree-based Clustering via Distance Ensemble and Kernelization”); ND-K :一种比较方法(Qiu 等人。“最近下降、树内和聚类”,arXiv:1412.5902v2,2014 年)。 注:a) ND-K 是 ND-Ward-E(KT) 的基础; b) 对于 ND.m,低版本 Matlab 中可能不存在函数“maxk”; 在这种情况下,可以使用 ND.m 中它后面的以下代码代替(我们在 ND.m 中突出显示了它)。 推荐方法介绍:ND-Ward-E(KT) 最近,我们提出了一种新的受物理启发的方法,称为最近下降(ND),它的作用是将所有样本组织成一个有效的图,称为 in-tree(图 1A)。 由于其有效的特性,这种 in-tree 证明非常适合数据

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