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DS-1000 / 871 / How can I perform regression in sklearn, using SVM and a polynomial kernel…

Problem

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Problem:

How can I perform regression in sklearn, using SVM and a polynomial kernel (degree=2)?
Note to use default arguments. Thanks.

A:

<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
</code>
predict = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Sklearn

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Source and history

upstream_id / Original problem ID
871
task_id
c4aabdcd-3aa3-5605-b265-d6fa3948d73b
task_key
default--test--871
task_revision_id
1
config / split
default / test

Official source

initial import