SUPPORT VECTOR CLASSIFIER VIA MATHEMATICA
Abstract
In this case study a Support Vector Classifier function has been developed in Mathematica. Starting with a brief summary of support vector classification method, the step by step implementation of the classification algorithm in Mathematica is presented and explained. To check our function, two test problems, learning a chess board and classification of two intertwined spirals are solved. In addition, an application to filtering of airborne digital land image by pixel classification is demonstrated using a new SVM kernel family, the KMOD, a kernel with moderate decreasing.
Keywords:
software Mathematica, kernel methods, pixel classification, remote sensingHow to Cite
Paláncz, B., Völgyesi, L. “SUPPORT VECTOR CLASSIFIER VIA MATHEMATICA”, Periodica Polytechnica Civil Engineering, 48(1-2), pp. 15–37, 2004.
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Section
Research Article