chore(deps): bump the python-compatible group in /ml-worker with 2 updates

[dependabot]

Bumps the python-compatible group in /ml-worker with 2 updates: pandas and pyod.

Updates pandas from 3.0.5 to 3.0.6

Release notes

Sourced from pandas's releases.

pandas 3.0.6

We are pleased to announce the release of pandas 3.0.6. This is a patch release in the 3.0.x series and includes some regression fixes and bug fixes. We recommend that all users of the 3.0.x series upgrade to this version. This is also the first release to support Python 3.15.

See the full whatsnew for a list of all the changes.

Pandas 3.0 supports Python 3.11 and higher. The release can be installed from PyPI:

python -m pip install --upgrade pandas==3.0.*

Or from conda-forge

conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Commits

• 2905718 RLS: 3.0.6
• 3188ced [backport 3.0.x] BUG: read_csv(sep=None) raised TypeError instead of falling...
• f097905 DOC: cleanup 3.0.6 whatsnew + mention Python 3.15 support (#68965) (#68969)
• 4f68223 [backport 3.0.x] BUG: fix setting with bool column mask into 1-column DataFra...
• e3df0e8 [backport 3.0.x] BUG: full-slice setitem into a pyarrow-backed array shared m...
• b7735f6 Backport PR #66117 on branch 3.0.x (BUG: interpolate leaving NAs unfilled for...
• bca0b77 [backport 3.0.x] BUG: read_csv leaked the string-intern table when a column f...
• bca1e5d [backport 3.0.x] BUG: prevent external mutation of RangeIndex._data (CoW) (#6...
• c95b42c [3.0.x] CI: skip cython-lint on pre-commit.ci (#68910)
• 9cbd884 [backport 3.0.x] Backport of some already merged regression fixes (#68447)
• Additional commits viewable in compare view

Updates pyod from 3.6.5 to 3.6.6

Release notes

Sourced from pyod's releases.

v3.6.6

PyOD 3.6.6

A maintenance release focused on estimator compatibility, numerical correctness, and documentation. No new detector or dependency is introduced.

Bug fixes

• LOCI: preserve the constructor parameter k for cloning and use contamination to derive the fitted threshold and binary labels. k still controls the radius-scan early stop. #707, fixes #194.
• Pearson correlation: compute all row pairs in the unweighted pearsonr_mat utility when there are more rows than features; previously some correlations incorrectly remained 1. #731.
• Deep-learning base class: return the fitted estimator from BaseDeepLearningDetector.fit. #740.
• VAE: preserve logvar_clip as supplied to the constructor so sklearn.clone works, while validating the training value separately. #738.
• Sampling: retain a fractional subset_size across fits instead of replacing the constructor argument with the first computed sample count. #737.
• Kernel PCA: forward the requested n_components to the underlying estimator. #730.
• KNN: allow supported brute-force metrics such as cosine without constructing an incompatible fallback BallTree. #729.
• DeepSVDD: suppress epoch-loss logging when verbose=0. #735.
• CLI: avoid falsely reporting Claude Code as installed merely because pyod install skill created its skill directory. Detection checks the executable or user configuration instead. #723, fixes #715.

Documentation and tests

• Remove the unsupported sample_weight entry from GMM.fit documentation. #741.
• Describe score_to_label as returning binary labels, not probabilities. #733.
• Repair KNN, LOF, and LUNAR reference links. #732.
• Clarify the ECOD/COPOD relationship. #725, addresses #655.
• Clarify LOCI's early-stop parameter, restore weighted Pearson range assertions, and seed the new rectangular-input regression fixture.
• Add regression coverage for estimator contracts, repeated fits, component forwarding, cosine distance, logging, contamination and rectangular correlations; make CLI detection tests independent of the host's installed executables.
• Retain the repository's existing CITATION.cff on master, alongside contributor-workflow ignore rules and the todo/ drop box.

Behavior notes

LOCI's binary labels now follow the documented contamination-based threshold rather than a fixed k cutoff. Raw LOCI scores for a fixed k are unchanged by this fix; tied scores can still make the labeled fraction differ from the requested contamination.

Kernel PCA scores can change when n_components is specified because the limit is now honored. Sampling refits with a fractional subset_size now use the current training-set size. Previously uncomputed Pearson row pairs now receive their actual correlation values.

The ROD duplicate-weighting proposal #746 is not included.

Contributors

Thanks to @​Mohit-Ak, @​VenishPaneliya, @​Iams4kura, @​busysofa15, @​godarrenw, and @​dishasharma23-prog.

Full changelog: v3.6.5...v3.6.6

Changelog

Sourced from pyod's changelog.

v<0.1.0>, <05/20/2018> -- Initial release. v<0.1.1>, <05/20/2018> -- Hot fixes for broken documentation. v<0.1.2>, <05/20/2018> -- Hot fixes for broken dependency. v<0.1.3>, <05/21/2018> -- Function Signature Improvement. v<0.2.0>, <05/23/2018> -- Implement tests and improve stability. v<0.2.1>, <05/23/2018> -- Remove data loading func due to broken dependency. v<0.2.2>, <05/24/2018> -- Refactor models and add more testcases v<0.2.3>, <05/26/2018> -- Add more testcases. v<0.3.0>, <05/27/2018> -- Provide full documentation. v<0.3.1>, <05/28/2018> -- Add more complete coverage for Py3.5+. v<0.3.2>, <05/29/2018> -- Implement fastABOD and added more documentations. v<0.3.3>, <05/29/2018> -- Urgent bug fix. v<0.3.4>, <05/29/2018> -- Another urgent bug fix. v<0.4.0>, <05/31/2018> -- Refactor all models to be sklearn compatible. v<0.4.1>, <06/01/2018> -- Support Python 2.7, 3.4, 3.5 and 3.6. v<0.4.2>, <06/01/2018> -- Fix Python 2.7 installation issue. v<0.4.3>, <06/02/2018> -- Add more models and refactored examples. v<0.4.4>, <06/03/2018> -- Refactor HBOS and add new models. v<0.4.5>, <06/04/2018> -- Implemented Feature Bagging meta framework. v<0.4.6>, <06/05/2018> -- Incremental changes and documentation improvements. v<0.4.7>, <06/06/2018> -- Add Principal Component Analysis (PCA) detector. v<0.4.8>, <06/07/2018> -- Refactor documentation and add test cases. v<0.4.9>, <06/09/2018> -- Add new utility functions and improve documentations. v<0.5.0>, <06/10/2018> -- Refactor models and improve documentation. v<0.5.1>, <06/12/2018> -- Add MCD detector and more Jupyter notebooks. v<0.5.2>, <06/13/2018> -- Incremental changes. v<0.5.3>, <06/14/2018> -- Incremental changes. v<0.5.4>, <06/18/2018> -- Add CBLOF model and incremental improvements. v<0.5.7>, <09/03/2018> -- Add AutoEncoder with fully connected architecture. v<0.5.8>, <09/04/2018> -- Remove keras, tensorflow and matplotlib as dependency. v<0.5.9>, <09/04/2018> -- Optimize models with numba for fast execution. v<0.6.0>, <10/19/2018> -- Update LOF due to the changes in sklearn 0.20.0. v<0.6.1>, <11/03/2018> -- Inclusion of Python 3.7 & welcome Zain Nasrullah. v<0.6.1>, <11/10/2018> -- Incremental changes and official release of 0.6.1. v<0.6.2>, <11/19/2018> -- Refactor base class to decrease cognitive complexity. v<0.6.2>, <11/24/2018> -- Add maintainability check and Appveyor CI. v<0.6.2>, <11/24/2018> -- Add LSCP implementation (WIP). v<0.6.3>, <11/26/2018> -- Move from README.md to README.rst. v<0.6.4>, <11/26/2018> -- Refactor version file for Python 2 compatibility. v<0.6.5>, <11/27/2018> -- Update README.rst Reference section. v<0.6.5>, <11/28/2018> -- Add Stochastic Outlier Selection (SOS). v<0.6.5>, <11/30/2018> -- Add CircleCI continuous integration. v<0.6.5>, <12/03/2018> -- Add Local Correlation Integral (LOCI). v<0.6.6>, <12/06/2018> -- Add LSCP (production version). v<0.6.6>, <12/08/2018> -- Add XGBOD. v<0.6.6>, <12/18/2018> -- Fixed bugs in CBLOF. v<0.6.6>, <12/18/2018> -- Refactor docstring from rst to numpydoc. v<0.6.6b1>, <12/18/2018> -- Pre-release of V0.6.6. v<0.6.6>, <12/21/2018> -- Redesign visualize function for all examples. v<0.6.6>, <12/23/2018> -- Refactor all docstring to numpydoc.

... (truncated)

Commits

• 3a71f47 Merge pull request #749 from yzhao062/development
• 97fa2b4 Prepare v3.6.6 maintenance release
• 87c9499 Iterate over rows in the unweighted branch of pearsonr_mat (#731)
• e357c5b Make LOCI honor contamination and keep k as a parameter (#707)
• 8d2eae3 fix: support cosine distance in KNN (#729)
• 033b964 Forward n_components in PyODKernelPCA (#730)
• 59f195b Stop Sampling.fit from overwriting subset_size (#737)
• fc5bbf2 Keep logvar_clip as given so VAE can be cloned (#738)
• 19fa982 Return self from BaseDeepLearningDetector.fit (#740)
• 109bdfd docs: clarify ECOD/COPOD relationship in docstrings (#655) (#725)
• Additional commits viewable in compare view

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[github-actions]

Dependency Review

✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.

OpenSSF Scorecard

Package	Version	Score	Details
pip/pandas	3.0.6	Unknown	Unknown
pip/pyod	3.6.6	Unknown	Unknown

Scanned Files

• ml-worker/requirements.txt