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run a multitude of classifiers on you data and get an AUC report

Results 14 polyssifier issues
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Bumps [numpy](https://github.com/numpy/numpy) from 1.19.5 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...

dependencies

Bumps [pillow](https://github.com/python-pillow/Pillow) from 8.4.0 to 9.0.1. Release notes Sourced from pillow's releases. 9.0.1 https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html Changes In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@​radarhere, @​hugovk] Restrict builtins within...

dependencies

Current exclusive support of binary classification is limiting the use of the tool. Multi-class problems arise frequently and it would be nice to be able to use polyssifier for multiclass...

dask-searchcv has optimized sklearn's default gridsearch in both local and cluster computing

We need to integrate imputation as part of the pipeline where the parameters of the imputation method can be searched in the grid search approach

There is an issue with feature plotting when feature selection is turned on.

Upgrading from Pandas 0.18 to 0.2 caused a shape error in predict_proba. The temporary fix in commit b17d13e9e4635278f00b6ab5eab150d3b2d52aad limits this implementation to binary classification only

Bumps [joblib](https://github.com/joblib/joblib) from 1.1.0 to 1.2.0. Changelog Sourced from joblib's changelog. Release 1.2.0 Fix a security issue where eval(pre_dispatch) could potentially run arbitrary code. Now only basic numerics are supported....

dependencies

Versions installed: Python 3.8.10 matplotlib==3.6.0 Error: ``` ValueError: rotation must be 'vertical', 'horizontal' or a number, not 90 ```

Versions installed: Python 3.8.10 scikit-learn==1.1.2 Warning: ``` lib/python3.8/site-packages/sklearn/ensemble/_forest.py:427: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or...