MAPLSC: A novel multi-class classifier for medical diagnosis
by Mingyu You, Rui-Wei Zhao, Guo-Zheng Li, Xiaohua Hu
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 5, No. 4, 2011

Abstract: Analysis of clinical records contributes to the Traditional Chinese Medicine (TCM) experience expansion and techniques promotion. More than two diagnostic classes (diagnostic syndromes) in the clinical records raise a popular data mining problem: multi-value classification. In this paper, we propose a novel multi-class classifier, named Multiple Asymmetric Partial Least Squares Classifier (MAPLSC). MAPLSC attempts to be robust facing imbalanced data distribution in the multi-value classification. Elaborated comparisons with other seven state-of-the-art methods on two TCM clinical datasets and four public microarray datasets demonstrate MAPLSC's remarkable improvements.

Online publication date: Sat, 24-Jan-2015

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