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University of Tennessee, Knoxville
Intelligent Data Mining; Kernel Functions; Regression Trees; Radial Basis Functions (RBFs); Support Vector Machines (SVM); and Information Criteria
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Intelligent Data Mining Using Kernel Functions And Information Criteria, Zhenqiu Liu
Intelligent Data Mining Using Kernel Functions And Information Criteria, Zhenqiu Liu
Doctoral Dissertations
Radial Basis Function (RBF) Neural Networks and Support Vector Machines (SVM) are two powerful kernel related intelligent data mining techniques. The current major problems with these methods are over-fitting and the existence of too many free parameters. The way to select the parameters can directly affect the generalization performance(test error) of theses models. Current practice in how to choose the model parameters is an art, rather than a science in this research area. Often, some parameters are predetermined, or randomly chosen. Other parameters are selected through repeated experiments that are time consuming, costly, and computationally very intensive. In this dissertation, …