Clustering Algorithm of Outliers Based on Adjacency Graph

Outliers are small pattern in data space. General clustering approaches,such as distance-based and statistics-based,are not adapted to classification of outliers because of their characteristic of fewness data and sparseness. This paper defines concepts of outlying shared attribute and outlying similarity based on the key attribute subspace of an outlier and proposes an analysis technique on β-cluster of outliers. An algorithm for clustering of outliers based on adjacency graph is put forward in this paper. Its main idea includes establishment and simplification of outlying adjacency graph in which a maximum complete subgraph is corresponding with a β-cluster of outliers. Examples and experimental results show that the algorithm is intuitionistic and well efficient.