test pr travis #2
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added 30 commits
October 27, 2017 13:35
Indeed, they do not add a significative speedup but have a high memory cost.
…py.special.logsumexp otherwise
added 21 commits
December 7, 2018 10:28
…zation: - fixed when to choose LinearDisciminantAnalysis when given 'auto' initialization - adapted the tests where 'lda' init can be set so that this cases will not return an error
# Conflicts: # doc/whats_new/v0.21.rst
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Feb 27, 2019
…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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Mar 21, 2019
* initial commit * used random class * fixed failing testcases, reverted __init__.py * fixed failing testcases #2 - passed rng as parameter to ParameterSampler class - changed seed from 0 to 42 (as original) * fixed failing testcases #2 - passed rng as parameter to SparseRandomProjection class * fixed failing testcases scikit-learn#4 - passed rng as parameter to GaussianRandomProjection class * fixed failing test case because of flake 8
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Oct 25, 2020
…scikit-learn#10591) * Initial add DET curve to classification metrics * Add DET to exports * Fix DET-curve doctest errors - Sample snippet in model_evaluation documentation was outdated. * Clarify wording in DET-curve computation - Align to the wording of ranking module to make it consistent. - Add correct describtion of input and outputs. - Update and fix non-existent links * Beautify DET curve documentation source - Limit line length to 80 characters. * Expand DET curve documentation - Add an example plot to show difference between ROC and DET curves. - Expand Usage Note section with background information and properties of DET curves. * Update DET-curve documentation - Fix typos and some grammar improvements. - Use named references to avoid potential conflicts with other sections. - Remove unneeded references and improved existing ones by using e.g. using versioned links. * Select relevant DET points using slice object * Remove some dubiety from DET curve doc-string * Add DET curve contributors * Add tests for DET curves * Streamline DET test by using parametrization * Increase verbosity of DET curve error handling - Explicitly sanity check input before computing a DET curve. - Add test for perfect scores. - Adapt indentation style to match the test module. * Add reference for DET curves in invariance test * Add automated invariance checks for DET curves * Resolve merge artifacts * Make doctest happy * Fix whitespaces for doctest * Revert unintended whitespace changes * Revert unintended white space changes #2 * Fix typos and grammar * Fix white space in doc * Streamline test code * Remove rebase artifacts * Fix PR link in doc * Fix test_ranking * Fix rebase errors * Fix import * Bring back newlines - Swallowed by copy/paste * Remove uncited ref link * Remove matplotlib deprecation warning * Bring back hidden reference * Add motivation to DET example * Fix lint * Add citation * Use modern matplotlib API Co-authored-by: Jeremy Karnowski <[email protected]> Co-authored-by: Julien Cornebise <[email protected]> Co-authored-by: Daniel Mohns <[email protected]>
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