Compactly supported graph building for spectral clustering

Abstract:

In spectral clustering approaches is of great importance how is built the graph representation over a data set, being reflected in the achieved clustering performance. In this work is introduced a methodology to build a graph representation of a given data, based on compactly supported radial basis functions which enables to highlight relevant pair-wise sample relationships. To tune such functions, an objective function is proposed, which aims to find a trade-off between a similarity and a sparsity measure, allowing to achieve a suitable local and global data structure representation. Synthetic and realworld data sets are tested. Results shows how proposed method improves clustering results, specially for an image segmentation task.

Año de publicación:

2014

Keywords:

Fuente:

scopus