Thanks to visit codestin.com
Credit goes to github.com

Skip to content

[MRG+1] Use the Gram Variant when precompute is True #3247

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Jun 5, 2014
Merged

[MRG+1] Use the Gram Variant when precompute is True #3247

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
37c65e5
FIX: Use coordinate_descent_gram when precompute is True | auto
MechCoder May 29, 2014
7b75ebb
FIX: Raise ValueError for invalid precompute
MechCoder Jun 5, 2014
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 10 additions & 3 deletions sklearn/linear_model/coordinate_descent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -467,12 +467,19 @@ def enet_path(X, y, l1_ratio=0.5, eps=1e-3, n_alphas=100, alphas=None,
coef_, l1_reg, l2_reg, X.data, X.indices,
X.indptr, y, X_sparse_scaling,
max_iter, tol, positive)
elif not multi_output:
elif multi_output:
model = cd_fast.enet_coordinate_descent_multi_task(
coef_, l1_reg, l2_reg, X, y, max_iter, tol)
elif isinstance(precompute, np.ndarray):
model = cd_fast.enet_coordinate_descent_gram(
coef_, l1_reg, l2_reg, precompute, Xy, y, max_iter,
tol, positive)
elif precompute is False:
model = cd_fast.enet_coordinate_descent(
coef_, l1_reg, l2_reg, X, y, max_iter, tol, positive)
else:
model = cd_fast.enet_coordinate_descent_multi_task(
coef_, l1_reg, l2_reg, X, y, max_iter, tol)
raise ValueError("Precompute should be one of True, False, "
"'auto' or array-like")
coef_, dual_gap_, eps_ = model
coefs[..., i] = coef_
dual_gaps[i] = dual_gap_
Expand Down
7 changes: 7 additions & 0 deletions sklearn/linear_model/tests/test_coordinate_descent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -460,6 +460,13 @@ def test_sparse_input_dtype_enet_and_lassocv():
assert_almost_equal(clf.coef_, clf1.coef_, decimal=6)


def test_precompute_invalid_argument():
X, y, _, _ = build_dataset()
for clf in [ElasticNetCV(precompute="invalid"),
LassoCV(precompute="invalid")]:
assert_raises(ValueError, clf.fit, X, y)


if __name__ == '__main__':
import nose
nose.runmodule()