45 lines
1.0 KiB
Python
45 lines
1.0 KiB
Python
"""
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===========================================
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SVM: Maximum separating margin hyperplane
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===========================================
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"""
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import numpy as np
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import pylab as pl
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from scikits.learn import svm
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# we create 40 separable points
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np.random.seed(0)
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X = np.r_[np.random.randn(20, 2) - [2,2], np.random.randn(20, 2) + [2, 2]]
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Y = [0]*20 + [1]*20
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# fit the model
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clf = svm.SVC(kernel='linear')
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clf.fit(X, Y)
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# get the separating hyperplane
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w = clf.coef_[0]
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a = -w[0]/w[1]
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xx = np.linspace(-5, 5)
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yy = a*xx - (clf.intercept_[0])/w[1]
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# plot the parallels to the separating hyperplane that pass through the
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# support vectors
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b = clf.support_[0]
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yy_down = a*xx + (b[1] - a*b[0])
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b = clf.support_[-1]
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yy_up = a*xx + (b[1] - a*b[0])
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# plot the line, the points, and the nearest vectors to the plane
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pl.set_cmap(pl.cm.Paired)
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pl.plot(xx, yy, 'k-')
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pl.plot(xx, yy_down, 'k--')
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pl.plot(xx, yy_up, 'k--')
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pl.scatter(X[:,0], X[:,1], c=Y)
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pl.scatter(clf.support_[:,0], clf.support_[:,1], marker='+')
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pl.axis('tight')
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pl.show()
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