wehub-resource-sync
43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
import logging
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try:
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from sklearn.model_selection import train_test_split
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except ImportError:
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from sklearn.cross_validation import train_test_split
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from sklearn.datasets import make_classification
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from mla.metrics.metrics import accuracy
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from mla.svm.kernerls import Linear, RBF
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from mla.svm.svm import SVM
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logging.basicConfig(level=logging.DEBUG)
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def classification():
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# Generate a random binary classification problem.
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X, y = make_classification(
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n_samples=1200,
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n_features=10,
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n_informative=5,
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random_state=1111,
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n_classes=2,
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class_sep=1.75,
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)
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# Convert y to {-1, 1}
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y = (y * 2) - 1
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X_train, X_test, y_train, y_test = train_test_split(
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X, y, test_size=0.2, random_state=1111
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)
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for kernel in [RBF(gamma=0.1), Linear()]:
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model = SVM(max_iter=500, kernel=kernel, C=0.6)
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model.fit(X_train, y_train)
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predictions = model.predict(X_test)
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print(
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"Classification accuracy (%s): %s" % (kernel, accuracy(y_test, predictions))
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)
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if __name__ == "__main__":
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classification()
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