Add another svm example.

This time with nonseparable data.

From: Fabian Pedregosa <fabian.pedregosa@inria.fr>

git-svn-id: https://scikit-learn.svn.sourceforge.net/svnroot/scikit-learn/trunk@560 22fbfee3-77ab-4535-9bad-27d1bd3bc7d8

examples/plot_svm_nonlinear.py

+
+import numpy as np
+import pylab as pl
+from scikits.learn import svm
+
+xx, yy = np.meshgrid(np.linspace(-5, 5), np.linspace(-5, 5))
+X = np.random.randn(300, 2)
+Y = np.logical_xor(X[:,0]>0, X[:,1]>0)
+
+# fit the model
+clf = svm.SVC(impl='nu_svc', kernel='rbf', C=100)
+clf.fit(X, Y)
+
+# plot the line, the points, and the nearest vectors to the plane
+Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
+Z = Z.reshape(xx.shape)
+
+pl.set_cmap(pl.cm.Paired)
+pl.pcolormesh(xx, yy, Z)
+pl.scatter(X[:,0], X[:,1], c=Y)
+
+pl.axis('tight')
+pl.show()
+