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LogisticRegression convert to float64 (for SAG solver) (scikit-learn#…
…13243) * Remove unused code * Squash all the PR 9040 commits initial PR commit seq_dataset.pyx generated from template seq_dataset.pyx generated from template #2 rename variables fused types consistency test for seq_dataset a sklearn/utils/tests/test_seq_dataset.py new if statement add doc sklearn/utils/seq_dataset.pyx.tp minor changes minor changes typo fix check numeric accuracy only up 5th decimal Address oliver's request for changing test name add test for make_dataset and rename a variable in test_seq_dataset * FIX tests * TST more numerically stable test_sgd.test_tol_parameter * Added benchmarks to compare SAGA 32b and 64b * Fixing gael's comments * fix * solve some issues * PEP8 * Address lesteve comments * fix merging * avoid using assert_equal * use all_close * use explicit ArrayDataset64 and CSRDataset64 * fix: remove unused import * Use parametrized to cover ArrayDaset-CSRDataset-32-64 matrix * for consistency use 32 first then 64 + add 64 suffix to variables * it would be cool if this worked !!! * more verbose version * revert SGD changes as much as possible. * Add solvers back to bench_saga * make 64 explicit in the naming * remove checking native python type + add comparison between 32 64 * Add whatsnew with everyone with commits * simplify a bit the testing * simplify the parametrize * update whatsnew * fix pep8
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