Scale-Invariance of Support Vector Machines based on the Triangular Kernel

This report focuses on the scale-invariance and the good performances of Support Vector Machines based on the triangular kernel. After a mathematica- l analysis of the scale-invariance of learning with that kernel, we illustrate its behavior with a simple 2D classification problem and compare its performances to those of a Gaussian kernel on face detection and handwritten character recognition

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