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Support Vector Classifier
Author

Béla Paláncz
Organization: Budapest University of Technology and Economics
Department: Photogrammetry and Geoinformatics
Revision date

2004-10-05
Description

In this case study, a Support Vector Classifier function has been developed in Mathematica. Starting with a brief summary of the support vector classification method, a step by step implementation of the classification algorithm is presented. Using this function, two test problems -- learning a chess board and classification of two interwined spirals -- are solved. In addition, an application to image recognition is demonstrated using wavelet transform as feature extraction method.
Subjects

*Mathematics > Calculus and Analysis > Differential Equations
*Mathematics > Probability and Statistics
Keywords

Computer vision, Bela Palancz
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SVCMathematica.nb (724.3 KB) - Mathematica Notebook