Example Classification
Written on July 20th, 2021 by control lab
In this example, we compared kernels for classification on circle data. As expected, the RBF kernel showed itself quite well, as well as the TKL.
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
from PMKLpy import PMKL
from myplots import *
X, y = PMKL.loadex1()
C = 1.0
SVM = PMKL.PMKL( C=C, to_print = False)
SVM.fit(X, y)
models = [svm.SVC(kernel='linear', C=C),
svm.SVC(kernel='rbf', gamma=0.7, C=C),
svm.SVC(kernel='poly', degree=3, gamma='auto', C=C)]
models = [clf.fit(X, y) for clf in models]
models.append(SVM)
# title for the plots
titles = ['SVC with linear kernel',
'SVC with RBF kernel',
'SVC with polynomial (degree 3) kernel',
'SVC with TKL kernel']
fig, sub = plt.subplots(1, 4, figsize = (25, 5))
plt.subplots_adjust(wspace=0.4, hspace=0.4)
X0, X1 = X[:, 0], X[:, 1]
xx, yy = make_meshgrid(X0, X1)
for clf, title, ax in zip(models, titles, sub.flatten()):
plot_contour_and_points(ax, clf, xx, yy, X0, X1, y, title, cmap=plt.cm.coolwarm, alpha=0.8)
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