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5. Variable Clustering via G-Models of Large Covariance Matrices

Variable Clustering via G-Models of Large Covariance Matrices

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：liming10060651088

【摘 要】

：

Clustering is one of the first tools to explore big data.Classical techniques,such as hierarchical clustering and k-means,are usually based on the closeness between two data points or between a data p

【作 者】

：

Florentina Bunea Christophe Giraud Xi Luo 

【机 构】

：

Cornell University,14853,USA Universite Paris-Sud

【出 处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

Variable clustering community estimation minimax lower bound copula models high 

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　　Clustering is one of the first tools to explore big data.Classical techniques,such as hierarchical clustering and k-means,are usually based on the closeness between two data points or between a data point to a cluster centroid.

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