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from sklearn import svm
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if 'features_train' not in locals() or globals():
%run ../dev/environment_setup.ipynb
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features_train_small = features_train[:len(features_train)/100]
labels_train_small = labels_train[:len(labels_train)/100]
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clf = svm.SVC(kernel='rbf')
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train_predict("Train and Predict Data with RBF Kernel Value")
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clf = svm.SVC(kernel='linear')
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train_predict("Train and Predict Data with Linear Kernel Value")