alibi-detect
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Algorithms for outlier, adversarial and drift detection
xgboost models under the sklearn interface are currently supportet by `ClassifierDrift(..., backend='sklearn')`. We should consider widening this support as @jklaise suggested in https://github.com/SeldonIO/alibi-detect/issues/642#issuecomment-1271451886: > Very likely outside the scope of...
Since `numba 0.56`, the `CVMDriftOnline` detector segfaults on MacOS (during our CI). See https://github.com/SeldonIO/alibi-detect/pull/573. I have done quite a bit of digging and can't find any out-of-bounds issues or other...
The tabular drift detector uses the KS and Chi^2 detectors for numerical and categorical features, respectively. This might however not be an appropriate choice for many use cases (e.g. sensitivity...
Updates the requirements on [packaging](https://github.com/pypa/packaging) to permit the latest version. Release notes Sourced from packaging's releases. 24.0 What's Changed Fix specifier matching when the specifier is long and has an...
Updates the requirements on [pytest-cov](https://github.com/pytest-dev/pytest-cov) to permit the latest version. Changelog Sourced from pytest-cov's changelog. 5.0.0 (2024-03-24) Removed support for xdist rsync (now deprecated). Contributed by Matthias Reichenbach in [#623](https://github.com/pytest-dev/pytest-cov/issues/623)...
Updates the requirements on [tensorflow-probability](https://github.com/tensorflow/probability) to permit the latest version. Release notes Sourced from tensorflow-probability's releases. TensorFlow Probability 0.24.0 Release notes This is the 0.24.0 release of TensorFlow Probability. It...
Updates the requirements on [tensorflow](https://github.com/tensorflow/tensorflow) to permit the latest version. Release notes Sourced from tensorflow's releases. TensorFlow 2.16.1 Release 2.16.1 TensorFlow TensorFlow Windows Build: Clang is now the default compiler...
Hi, Could you add support for Pandas DataFrame inputs in the model? It would make data preprocessing much easier for those of us using pandas. Thanks!