Skip to content

DOC fix description of tolerance in OMP #26823

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
Jul 12, 2023
Merged

DOC fix description of tolerance in OMP #26823

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
1f0df42
DOC fix description of tolerance in OMP
fuglede Jul 12, 2023
bf16a93
DOC fix OMP documentation line length being too long
fuglede Jul 12, 2023
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
7 changes: 4 additions & 3 deletions sklearn/linear_model/_omp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -332,7 +332,7 @@ def orthogonal_mp(
default) this value is set to 10% of n_features.

tol : float, default=None
Maximum norm of the residual. If not None, overrides n_nonzero_coefs.
Maximum squared norm of the residual. If not None, overrides n_nonzero_coefs.

precompute : 'auto' or bool, default=False
Whether to perform precomputations. Improves performance when n_targets
Expand Down Expand Up @@ -493,7 +493,8 @@ def orthogonal_mp_gram(
default) this value is set to 10% of n_features.

tol : float, default=None
Maximum norm of the residual. If not `None`, overrides `n_nonzero_coefs`.
Maximum squared norm of the residual. If not `None`,
overrides `n_nonzero_coefs`.

norms_squared : array-like of shape (n_targets,), default=None
Squared L2 norms of the lines of `y`. Required if `tol` is not None.
Expand Down Expand Up @@ -625,7 +626,7 @@ class OrthogonalMatchingPursuit(MultiOutputMixin, RegressorMixin, LinearModel):
default) this value is set to 10% of n_features.

tol : float, default=None
Maximum norm of the residual. If not None, overrides n_nonzero_coefs.
Maximum squared norm of the residual. If not None, overrides n_nonzero_coefs.

fit_intercept : bool, default=True
Whether to calculate the intercept for this model. If set
Expand Down