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The SVM pair plots for polynomial and radial kernels are homogeneous and therefore not helpful for assessing the fits.
The slice argument for plot.svm specifies to which constants the other dimensions should be held, that is, which 2-D hyperplane the data are projected onto for visualization. The default is zero, which may give a hyperplane that does not intersect with the decision boundary. Setting the slice argument to the medians of the other dimensions ensures the hyperplane the data are projected onto is near the data and intersects the decision boundary. The intersection of the boundary and the hyperplane may not perfectly partition data projected from higher dimensions, but it might indicate, for example, appropriate curvature, or provide ideas to improve the fit.
The text was updated successfully, but these errors were encountered:
The SVM pair plots for polynomial and radial kernels are homogeneous and therefore not helpful for assessing the fits.
The slice argument for plot.svm specifies to which constants the other dimensions should be held, that is, which 2-D hyperplane the data are projected onto for visualization. The default is zero, which may give a hyperplane that does not intersect with the decision boundary. Setting the slice argument to the medians of the other dimensions ensures the hyperplane the data are projected onto is near the data and intersects the decision boundary. The intersection of the boundary and the hyperplane may not perfectly partition data projected from higher dimensions, but it might indicate, for example, appropriate curvature, or provide ideas to improve the fit.
The text was updated successfully, but these errors were encountered: