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2 files changed

+1
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skglm/estimators.py

Lines changed: 0 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -101,11 +101,6 @@ def _glm_fit(X, y, model, datafit, penalty, solver):
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n_samples, n_features = X_.shape
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104-
# if issparse(X):
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# datafit.initialize_sparse(X_.data, X_.indptr, X_.indices, y)
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# else:
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# datafit.initialize(X_, y)
108-
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# if model.warm_start and hasattr(model, 'coef_') and model.coef_ is not None:
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if solver.warm_start and hasattr(model, 'coef_') and model.coef_ is not None:
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if isinstance(datafit, QuadraticSVC):
@@ -1373,12 +1368,6 @@ def fit(self, X, y):
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fit_intercept=False,
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)
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# # solve problem
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# if not issparse(X):
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# datafit.initialize(X, y)
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# else:
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# datafit.initialize_sparse(X.data, X.indptr, X.indices, y)
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w, _, stop_crit = solver.solve(X, y, datafit, penalty)
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# save to attribute

skglm/solvers/base.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -137,7 +137,7 @@ def solve(
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if run_checks:
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self._validate(X, y, datafit, penalty)
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# check for None as GramCD solver doesn't take None as datafit
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# check for None as `GramCD` solver take `None` as datafit
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if datafit is not None and initialize_datafit:
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if issparse(X):
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datafit.initialize_sparse(X.data, X.indptr, X.indices, y)

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