A Study on Sequential Extraction of Clusters using Noise Clustering based on Local Outlier Factor

Abstract

Noise Clustering based on Local Outlier Factor (NCLOF) is a robust clustering method against outliers that adjusts dissimilarity according to the value of Local Outlier Factor (LOF), which indicates the degree of data outliers. In this study, we propose an extension of NCLOF to a sequential extraction method. The sequential extraction method is a method that extracts clusters one by one, eliminating the need to specify the number of clusters in advance. Numerical experiments were conducted on several datasets, and the results were compared with those of existing methods. The results of the numerical experiments show that the proposed method is as good as or better than the existing methods.