ECML PKDD 2008
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
15 - 19 September 2008, Antwerp, Belgium
Paper abstractClustering via Local RegressionJun Sun - Institute of Software, Chinese Academy of Sciences, ChinaZhiyong Shen - Institute of Software, Chinese Academy of Sciences, China Hui Li - Graduate University, Chinese Academy of Sciences, China Yidong Shen - Institute of Software, Chinese Academy of Sciences, China Session: Clustering 1 Springer Link: http://dx.doi.org/10.1007/978-3-540-87481-2_30 This paper deals with the local learning approach for clustering, which is based on the idea that in a good clustering, the cluster label of each data point can be well predicted based on its neighbors and their cluster labels. We propose a novel local learning based clustering algorithm using kernel regression as the local label predictor. Although sum of absolute error is used instead of sum of squared error, we still obtain an algorithm that clusters the data by exploiting the eigen-structure of a sparse matrix. Experimental results on many data sets demonstrate the effectiveness and potential of the proposed method. |