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Searched refs:sparse_X (Results 1 – 9 of 9) sorted by relevance

/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/preprocessing/tests/
H A Dtest_polynomial.py520 sparse_X, argument
524 if sparse_X:
525 X = sparse_X(X)
530 if sparse_X:
594 sparse_X, argument
598 if sparse_X:
599 X = sparse_X(X)
604 if sparse_X:
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/svm/tests/
H A Dtest_bounds.py14 sparse_X = sp.csr_matrix(dense_X) variable
25 Xs = {"sparse": sparse_X, "dense": dense_X}
/dports/misc/orange3/orange3-3.29.1/Orange/tests/
H A Dtest_domain.py519 self.assertFalse(conversion.sparse_X)
528 self.assertTrue(conversion.sparse_X)
537 self.assertTrue(conversion.sparse_X)
/dports/math/py-hdbscan/hdbscan-0.8.27/hdbscan/tests/
H A Dtest_hdbscan.py587 sparse_X = sparse.csr_matrix(X)
589 labels = HDBSCAN().fit(sparse_X).labels_
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/linear_model/tests/
H A Dtest_ridge.py442 (solver, sparse_X)
443 for (solver, sparse_X) in product(
447 if not (sparse_X and solver not in ["sparse_cg", "ridgecv"])
457 solver, proportion_nonzero, n_samples, dtype, sparse_X, seed, normalize argument
477 if sparse_X:
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/feature_selection/tests/
H A Dtest_feature_select.py103 sparse_X = _convert_container(X, "sparse")
105 sparse_corr_coeffs = r_regression(sparse_X, y, center=center)
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/linear_model/
H A D_coordinate_descent.py65 sparse_X = sparse.issparse(X)
69 if sparse_X:
/dports/misc/orange3/orange3-3.29.1/Orange/data/
H A Ddomain.py93 self.sparse_X = should_be_sparse(destination.attributes)
H A Dtable.py324 destination.attributes, conversion.sparse_X,
2134 target.X = match_density[conversion.sparse_X](target.X)