Title:
SVM_GUI_3.1[mcode]{by-faruto}
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Description: Support Vector Machine SVM (Support Vector Machine) as a trainable machine learning methods, relying on small samples after learning Navstar extract model parameters can be distributed uniformly and greatly reduced the number of stars the guide star. Basic Vapnik et al in years of study on the basis of statistical learning theory, linear classifier proposed an alternative design best practices. The principle is also linearly separable from talking, and then extended to the case of non-linear. Even extended to use a nonlinear function to go, this classification is known as support vector machines (Support Vector Machine, referred SVM). Support vector machine made a deep theoretical background. Support Vector Machine method is a new method proposed in recent years.
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SVM_GUI_3.1[mcode]{by faruto}\readme.txt
.............................\SVC.fig
.............................\SVC.m
.............................\SVM_GUI.fig
.............................\SVM_GUI.m
.............................\SVR.fig
.............................\SVR.m
.............................\testdata\fisheriris_test.mat
.............................\........\regress_test.mat
.............................\........\wine_test.mat
.............................\testdata
SVM_GUI_3.1[mcode]{by faruto}
