def test_SVR():
"""
Test Support Vector Regression
"""
clf = svm.SVR(kernel='linear')
clf.fit(X, Y)
pred = clf.predict(T)
assert_array_almost_equal(clf.dual_coef_, [[-0.1, 0.1]])
assert_array_almost_equal(clf.coef_, [[0.2, 0.2]])
assert_array_almost_equal(clf.support_vectors_, [[-1, -1], [1, 1]])
assert_array_equal(clf.support_, [1, 3])
assert_array_almost_equal(clf.intercept_, [1.5])
assert_array_almost_equal(pred, [1.1, 2.3, 2.5])
# the same with kernel='rbf'
clf = svm.SVR(kernel='rbf')
clf.fit(X, Y)
pred = clf.predict(T)
assert_array_almost_equal(clf.dual_coef_,
[[-0.014, -0.515, -0.013, 0.515, 0.013, 0.013]],
decimal=3)
assert_raises(NotImplementedError, lambda: clf.coef_)
assert_array_almost_equal(clf.support_vectors_, X)
assert_array_almost_equal(clf.intercept_, [1.49997261])
assert_array_almost_equal(pred, [1.10001274, 1.86682485, 1.73300377])
def test_SVR():
"""
Test SVM regression
"""
clf = svm.SVR(kernel='linear')
clf.fit(X, Y)
pred = clf.predict(T)
assert_array_almost_equal(clf.dual_coef_, [[-0.1, 0.1]])
assert_array_almost_equal(clf.coef_, [[0.2, 0.2]])
assert_array_almost_equal(clf.support_, [[-1, -1], [1, 1]])
assert_array_almost_equal(clf.intercept_, [1.5])
assert_array_almost_equal(pred, [1.1, 2.3, 2.5])
# the same with kernel='rbf'
clf = svm.SVR(kernel='rbf')
clf.fit(X, Y)
pred = clf.predict(T)
assert_array_almost_equal(clf.dual_coef_,
[[-0.01441007, -0.51530606, -0.01365979,
0.51569493, 0.01387495, 0.01380604]])
assert_raises(NotImplementedError, lambda: clf.coef_)
assert_array_almost_equal(clf.support_, X)
assert_array_almost_equal(clf.intercept_, [ 1.49997261])
assert_array_almost_equal(pred, [ 1.10001274, 1.86682485, 1.73300377])
def svm_reg(algo={},tmp={},testset={},X=None,Y=None):
print "svm_reg"
svr_poly=svm.SVR(kernel="linear")
pred=svr_poly.fit(X,Y).predict(X)
RMSE2(pred=pred,test=Y);
