B2028
Title: Model-based clustering for large scale data with a massive null group
Authors: Soohyun Ahn - Ajou University (Korea, South) [presenting]
Abstract: A new clustering method for large scale data with a massive null group is proposed and called self-semi-supervised clustering. Self-semi-supervised clustering is a two-stage procedure: pre-select a part of ``null'' group from the data in the first stage and apply semi-supervised clustering to the rest of the data in the second stage, allowing them to be assigned to the null group. We evaluate the performance of the proposed method using a simulation study.
