title: A note on hyper ellipse method for classifying biological and medical data.
abstract: The classification of biological and medical datasets is essential to humanity. This study proposes a hyper ellipse method based on mixed integer nonlinear program for classifying datasets. A linearization technique with a number of piecewise line segments is used to treat nonlinear constraints, which aims to obtain an approximate optimal solution. Numerical examples are presented to demonstrate the efficacy of the proposed method.
authors.affiliation: Institute of Information Management, National Chiao Tung University, Hsinchu 300, Taiwan, ROC. Electronic address: yaohuei.huang@gmail.com.
authors.forename: Yao-Huei
authors.initials: YH
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual / Q000145:classification*; D007498:Iris; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D018139:Simplexvirus; D046388:Swallows
keywords: Hyper ellipse; Linearization; Nonlinear program