nmi指数matlab代码-Clustering-by-InTree-Ensemble-PR2020:"EnhancingIn-Tree-ba
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
文件下载
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本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明