Non-linear SVMΒΆ
Perform binary classification using non-linear SVC with RBF kernel. The target to predict is a XOR of the inputs.
Python source code: plot_svm_nonlinear.py
print __doc__
import numpy as np
import pylab as pl
from scikits.learn import svm
xx, yy = np.meshgrid(np.linspace(-5, 5, 500), np.linspace(-5, 5, 500))
np.random.seed(0)
X = np.random.randn(300, 2)
Y = np.logical_xor(X[:,0]>0, X[:,1]>0)
# fit the model
clf = svm.NuSVC()
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()