核逼近(Kernel Approximation)

Posted 2021-05-25 Data+Science+Insight

核逼近(Kernel Approximation)

 

主要方法和函数：

sklearn.kernel_approximation.Nystroem

sklearn.kernel_approximation.AdditiveChi2Sampler

sklearn.kernel_approximation.RBFSampler

sklearn.kernel_approximation.SkewedChi2Sampler

 

>>> from sklearn.kernel_approximation import SkewedChi2Sampler
>>> from sklearn.linear_model import SGDClassifier
>>> X = [[0, 0], [1, 1], [1, 0], [0, 1]]
>>> y = [0, 0, 1, 1]
>>> chi2_feature = SkewedChi2Sampler(skewedness=.01,
...                                  n_components=10,
...                                  random_state=0)
>>> X_features = chi2_feature.fit_transform(X, y)
>>> clf = SGDClassifier(max_iter=10, tol=1e-3)
>>> clf.fit(X_features, y)  
SGDClassifier(alpha=0.0001, average=False, class_weight=None,
       early_stopping=False, epsilon=0.1, eta0&