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The Entire Regularization Path for the Support Vector Machine

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Figure

Figure 1: A simple example shows the elements of a SVM model. The “+1” points are solid,the “-1” hollow
Figure 2: The hinge loss penalizes observation margins yf(x) less than +1 linearly, and is indiffer-ent to margins greater than +1
Figure 3: Simulated data illustrate the need for regularization. The 200 data points are generatedfrom a pair of mixture densities
Figure 4: Test error curves for the mixture example, using four different values for the radial kernelparameter γ
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