Rishi Dua
33 linhas
760 B
Python
33 linhas
760 B
Python
import time
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import sys
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import numpy
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import vector
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from sklearn.svm import SVR
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from sklearn.cross_validation import train_test_split
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usage = "filename features_file labels_file output_file"
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if __name__ == "__main__":
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if (len(sys.argv)!=5):
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print usage
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else:
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file_x = sys.argv[1]
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file_y = sys.argv[2]
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file_out = sys.argv[3]
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split_seed = sys.argv[4]
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X = numpy.genfromtxt(file_x, delimiter=' ')
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y = numpy.genfromtxt(file_y, delimiter=' ')
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# Split the data into training/testing sets
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=split_seed)
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#support vector regression
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svr = SVR(kernel='linear', C=1e3)
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svr.fit(X, y)
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y_predict=svr.predict(X_test)
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numpy.savetxt(file_out, y_predict)
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