[pull] master from stanfordmlgroup:master #1
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…les/user-guide/nokogiri-1.10.8 Bump nokogiri from 1.10.4 to 1.10.8 in /examples/user-guide
fix classification sample code
Get long description from README.md
* Add py311, remove py37 * Fix minor linting errors on new pylint * Fix types; remove comment * Set seed for deterministic tests * Fix types in test file * Fix unused import; Use specific noqa codes; Fix typo in pre-commit config * Fix type in tests * Fix feature importance base case * xfail test per https://github.com/stanfordmlgroup/ngboost/pull/320\#issuecomment-1885234861 --------- Co-authored-by: Jack McIvor <j.mcivor@draftkings.com>
Fix issue causing large memory consumption in pred_dist()
* Add support for python 3.12 * Drop support for python 3.9 * Bump flake8 and pylint
Release 0.5.0
* Implemented NormalFixedMean * Added NormalFixedVar and NormalFixedMean to test_distns.py * Match log(sigma) parameterization of Normal class * Update __init__.py Linter is demanding a blank line for ending a file (sigh)
Makefile updates and adding support for FixedNormalMean
feat: Add estimator type with reg and clf for NGBClassifier and NGBRegressor
* Update partial_fit to respect validation data Existing logic ignores passed validation data, the if erarly_stopping_rounds control sequence is updated to respect the passed validation data. Co-authored-by: jerome-f <irudayaf@sc1nc008is02.eth.rsiec.sc1.science.roche.com>
* v0.5.5 release
The two parameters `validation_fraction` and `early_stopping_rounds` have been added to the `params` dictionary.
Update parameters in `get_params`
Co-authored-by: Mahmoud <mhegab@raisaenergy.com>
feat: added Weibull distribution
* Update dev dependencies and improve pyproject.toml configuration - Update dev dependencies to latest versions: - pytest: ^6.1.2 → ^8.0.0 - black: ^22.8.0 → ^24.0.0 - pre-commit: ^2.0 → ^4.0.0 - isort: ^5.6.4 → ^5.13.0 - pylint: ^3.0.3 → ^3.2.0 - flake8: ^7.0.0 → ^7.1.0 - Migrate to modern Poetry format: [tool.poetry.dev-dependencies] → [tool.poetry.group.dev.dependencies] - Add [tool.black] configuration with explicit line length and target versions - Improve Python version markers for numpy/scipy using PEP 508 markers Closes #379 * Fix Black target-version configuration Remove py312 and py313 from target-version as they're not supported by the current Black version in CI environment * Update pre-commit configuration - Update Black version from 22.8.0 to 24.10.0 to match pyproject.toml - Fix deprecated default_stages: commit -> pre-commit * Apply linting fixes - Apply Black formatting changes (blank lines after docstrings) - Update code formatting to match updated linter configuration * Update pre-commit-hooks to v6.0.0 - Fix deprecated stage names warning - Update from v2.2.3 to v6.0.0 to use modern pre-commit hooks * update release
* Fix NumPy 2.x natural gradient compatibility issue - Replace vectorized np.linalg.solve with sample-wise computation in scores.py - Add robust dimension checking and error handling - Handle singular matrix cases with pseudo-inverse fallback - Add comprehensive test suite for NumPy 2.x compatibility - Fixes GitHub issue #384: dimension mismatch in natural gradient computation The original issue occurred when np.linalg.solve received incompatible dimensions between metric and gradient arrays. The new implementation: 1. Validates dimensions before computation 2. Solves linear systems sample-by-sample for better stability 3. Provides clear error messages for dimension mismatches 4. Handles singular matrices gracefully All existing tests pass and new compatibility tests verify the fix. * fix veresion * Fix linting issues in test_numpy2_compatibility.py - Fix unbalanced tuple unpacking in make_regression call - Replace broad Exception catching with specific ValueError and LinAlgError - All linter checks now pass * Fix trailing whitespace in scores.py - Remove trailing whitespace that was causing GitHub CI to fail - All linter checks now pass on Python 3.11 * tests: make_regression unpack (X, y) for sklearn compatibility across versions * tests: request coef=True in make_regression and unpack 3 values to satisfy pylint unbalanced-tuple-unpacking across sklearn versions * Fix natural gradient shape handling without performance hit * Delete .evn
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