Cost functions for pairwise data clustering

被引：4

作者：

Angelini, L

Nitti, L

Pellicoro, M

Stramaglia, S

机构：

[1] Univ Bari, Dipartimento Fis, I-70126 Bari, Italy

[2] Univ Bari, DETO Sez Fis Med, I-70124 Bari, Italy

[3] Ist Nazl Fis Nucl, Sez Bari, I-70126 Bari, Italy

来源：

PHYSICS LETTERS A | 2001年 / 285卷 / 5-6期

关键词：

Learning systems - Ground state - Clustering algorithms;

D O I：

10.1016/S0375-9601(01)00373-5

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Cost functions for nun-hierarchical pairwise clustering are introduced, in the probabilistic autoencoder framework, by the request of maximal average similarity between input and the output of the autoencoder. Clustering is thus formulated as the problem of finding the ground state of Potts spins Hamiltonians. The partition, provided by this procedure, identifies clusters with dl:nse connected regions in the data space. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：279 / 285

页数：7

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