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from sklearn import svm
#X-> training inputs
#Y-> training outputs
# Here we are training a binary classifier
X = [[1, 0, 2], [0, 1, 3]]
y = [0, 1]
##SVM with setting kernel='linear'
##By default we all have kernel='RBF'
clf = svm.SVC(kernel='linear', C=1)
clf.fit(X, y)
#Output
SVC(C=1, cache_size=200, class_weight=None, coef0=0.0,
decision_function_shape=None, degree=3, gamma='auto', kernel='linear',
max_iter=-1, probability=False, random_state=None, shrinking=True,
tol=0.001, verbose=False)
clf.predict([[2., 2., 2.]])
Out[7]:
array([0])
Here “LinearSVC” has no parameter kernel as by default it is linear.
In [8]:
lin_clf = svm.LinearSVC(kernel='linear', C=1)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-8-08a26ddf4f5d> in <module>()
----> 1 lin_clf = svm.LinearSVC(kernel='linear', C=1)
TypeError: __init__() got an unexpected keyword argument 'kernel'
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