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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
Does scikit-learn provide facility to use SVM for regression, using a gaussian kernel? I looked at the APIs and I don't see any. Has anyone built a package on top of scikit-learn that does this?
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Python Code:
import numpy as np
import pandas as pd
import sklearn
X, y = load_data()
assert type(X) == np.ndarray
assert type(y) == np.ndarray
# fit, then predict X
from sklearn.svm import SVR
svr_rbf = SVR(kernel='rbf')
svr_rbf.fit(X, y)
predict = svr_rbf.predict(X)
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