A Novel Metric Embedding Optimal Normalization Mechanism for Clustering of Series Data
Shigeyuki Mitsui, Katsutoshi Sakata, Hiroya Nobori, S. KOMATSU · IEICE Transactions on Information and Systems · 2008
Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.