发明名称 |
Model selection for cluster data analysis |
摘要 |
A model selection method is provided for choosing the number of clusters, or more generally the parameters of a clustering algorithm. The algorithm is based on comparing the similarity between pairs of clustering runs on sub-samples or other perturbations of the data. High pairwise similarities show that the clustering represents a stable pattern in the data. The method is applicable to any clustering algorithm, and can also detect lack of structure. We show results on artificial and real data using a hierarchical clustering algorithm.
|
申请公布号 |
US2005071140(A1) |
申请公布日期 |
2005.03.31 |
申请号 |
US20040478191 |
申请日期 |
2004.11.01 |
申请人 |
BEN-HUR ASA;ELISSEEFF ANDRE;GUYON ISABELLE |
发明人 |
BEN-HUR ASA;ELISSEEFF ANDRE;GUYON ISABELLE |
分类号 |
G06F19/00;G06G7/48;G06G7/58;G06K9/62;(IPC1-7):G06G7/48 |
主分类号 |
G06F19/00 |
代理机构 |
|
代理人 |
|
主权项 |
|
地址 |
|