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Include ElasticNet like regularization for SparseLogisticRegression #244

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Include ElasticNet like regularization for SparseLogisticRegression #244

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4563f22
Altered Quadratic class
Apr 10, 2024
0f21cdf
Include ElasticNet like regularization for SparseLogisticRegression
Apr 10, 2024
85e26c1
Revert "Altered Quadratic class"
Apr 10, 2024
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5 changes: 3 additions & 2 deletions skglm/estimators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1003,10 +1003,11 @@ class SparseLogisticRegression(LinearClassifierMixin, SparseCoefMixin, BaseEstim
Number of subproblems solved to reach the specified tolerance.
"""

def __init__(self, alpha=1.0, tol=1e-4, max_iter=20, max_epochs=1_000, verbose=0,
def __init__(self, alpha=1.0, l1ratio=0.5, tol=1e-4, max_iter=20, max_epochs=1_000, verbose=0,
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You need to add a description of this parameter in the docstring above; also, call it l1_ratio for compatibility with sklearn.

fit_intercept=True, warm_start=False):
super().__init__()
self.alpha = alpha
self.l1ratio = l1ratio
self.tol = tol
self.max_iter = max_iter
self.max_epochs = max_epochs
Expand Down Expand Up @@ -1035,7 +1036,7 @@ def fit(self, X, y):
max_iter=self.max_iter, max_pn_iter=self.max_epochs, tol=self.tol,
fit_intercept=self.fit_intercept, warm_start=self.warm_start,
verbose=self.verbose)
return _glm_fit(X, y, self, Logistic(), L1(self.alpha), solver)
return _glm_fit(X, y, self, Logistic(), L1_plus_L2(self.alpha,self.l1ratio), solver)
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this is not PEP8 compliant, by convention you need to add a space after the comma. You can configure your editor to do it automatically : https://github.com/mathurinm/github-assignment/?tab=readme-ov-file#vscode-configuration


def predict_proba(self, X):
"""Probability estimates.
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