Methodology

In this section, the proposed clustering algorithm is introduced. The main idea of the algorithm depends on three main stages. At the first stage, data is partitioned into small dense partitions during the consecutive processing of data dimensions. Second stage removes noise samples based on the estimated dimensional density of each detected partition. At the last stage, remaining dense partitions are merged to form final clusters. These stages are explained in the following sections.