8000 [MRG] FIX: Allow coef_=None with warm_start=True in MultiTaskElasticNet by larsoner · Pull Request #12844 · scikit-learn/scikit-learn · GitHub
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[MRG] FIX: Allow coef_=None with warm_start=True in MultiTaskElasticNet #12844

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[MRG] FIX: Allow coef_=None with warm_start=True in MultiTaskElasticNet #12844

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2 changes: 1 addition & 1 deletion sklearn/linear_model/coordinate_descent.py
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Expand Up @@ -1797,7 +1797,7 @@ def fit(self, X, y):
X, y, X_offset, y_offset, X_scale = _preprocess_data(
X, y, self.fit_intercept, self.normalize, copy=False)

if not self.warm_start or not hasattr(self, "coef_"):
if not self.warm_start or getattr(self, "coef_", None) is None:
self.coef_ = np.zeros((n_tasks, n_features), dtype=X.dtype.type,
order='F')

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3 changes: 2 additions & 1 deletion sklearn/linear_model/tests/test_coordinate_descent.py
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Expand Up @@ -405,7 +405,8 @@ def test_multi_task_lasso_and_enet():
assert 0 < clf.dual_gap_ < 1e-5
assert_array_almost_equal(clf.coef_[0], clf.coef_[1])

clf = MultiTaskElasticNet(alpha=1.0, tol=1e-8, max_iter=1)
clf = MultiTaskElasticNet(alpha=1.0, tol=1e-8, max_iter=1, warm_start=True)
clf.coef_ = None # ensure that this is still supported with warm_start
assert_warns_message(ConvergenceWarning, 'did not converge', clf.fit, X, Y)


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