Self-semi-supervised clustering for large scale data with massive null group - Ahn, Soohyun; Choi, Hyungwon; Lim, Johan; Lee, Kyeong Eun (Journal of the Korean Statistical Society, 2020)
In this paper, we propose self-semi-supervised clustering, a new clustering method for large scale data with a massive null group. Self-semi-supervised clustering is a two-stage procedure: preselect 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 and demonstrate the method in the analysis of time course gene expression data from a longitudinal study of Influenza A virus infection.
Keywords: Influenza A virus; Massive null group; Model-based clustering; Pre-selection; Semi-supervised clustering; Time-course microarray data