Partial dependence plots #721
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…gorical features.
…ethod falls to predict_proba.
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RobertSamoilescu
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Sep 2, 2022
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| logger.warning('The length of `target_names` does not match the number of predicted outputs. ' | ||
| 'Ensure that the lengths match, otherwise a call to the `plot_pd` method might ' | ||
| 'raise an error or produce undesired labeling.') |
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I don't think there is a possibility to check whether the number of targets that we computed the PD/ICE for matches the length of target_names without a dummy call. Altough the user should be aware of that I decided to include a warning message in case that happens. Shall we go even further and raise an error?
…um-cat, sharey num-cats, updated images.
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Following an offline discussion it was decided to simplify the implementation and user interface by splitting the implementation into two distinct classes:
This allows us to remove all of the slightly confusing arguments discussed previously. Also, @RobertSamoilescu checked that the recursive algorithm returns slightly different values than performing the brute-force PD on the same estimators which further justifies splitting the implementation into two public classes (similar to |
jklaise
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Sep 8, 2022
jklaise
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Sep 8, 2022
… docs for helper plotting functions.
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* Partial API & docs * included sanity checks, grid construction for both numerical and categorical features. * Finalized explain and build_explanation. Included one feature numerical plots. * included kwargs for all kinds of plots * Implemented plotting functionality for every feature types and combinations. * Fixed share y axis * Minor plot fixes. * Minor refactoring. Docstring for PartialDependece class * Docstring for plotting function. Minor grammar corrections. * Included test for sanity check. To be cleaned and optimized. * Partial cleaning of the tests. * Finalized params sanity checks tests. * Included test for number of features. * Test explanation shapes for numerical features. * Included black-box wrapper for classification and regression & corresponding tests * Included a PD simple example. * Included Adult example. Minor one way numerical plot fix for labels. * Solved flak8 warnings * Solved mypy errors. * Improved docs for plots. * Some comments and TODOs. * included list of TODOs * Consider by default all single features to compute the pd for. * Included custom grid_points. * Updated categorical graph from barplot to lineplot. * Included two target outputs for binary classification when response_method falls to predict_proba. * Solved flake8 warnings. * Solved mypy errors. * isort and mypy * Fixed fitted check for older versions of sklearn. * Cleaned the docs for partial_dependence.py * Tuple in numpy/list inconsistency * Reintroducing seaborn because of the heatmap * Introduced contour plots levels args. * minor changes to the docs * Started pdp bike dataset example * Included argument to display custom number of ice curves. * Unfinished example PD bike dataset * Finalized partial dependece bike example. * Draft method description. Some variable renaming. * Refactoring - explanation object. * Updated docs entries. * Readme indentation * setup.py minor correction * Minor documentation corrections * Removed initial pd exampled notebook * Changed links to Introduction section * Revert "Changed links to Introduction section" This reverts commit 67dce6f. * Fix problem with equation in method docs * Included test for pd computation against the sklearn implementation for numerical and adapted categorical features. * Addressed comments - part 1 * Addressed comments - part 2 * Removed seed. * Included progress bar while explaining features * A few changes to the pdp example notebook. * Removed ipynb for examples. * Addressed notebook comments. * Addressed comments regarding the plots. * Removed meta from data field. * Literal for some arguments * Allow 2 way PDP for kind both. Improved method description. Cleaned example. * Minor cleaning. * Updated docs in the method description. * Corrections to the example text. * Minor punctuation correction in the method description. * Removed features_list from method notebook * Update link: latest with stable * Changed kernel env back to Python. * Minor docstrings correction. * Fixed spelling error in example notebook. * Replaced centered with center. Improved docs for center flag. * Removed seaborn from dependencies. Implemented on matplotlib heatmap. * Included clarification for the response_method. * Replaced sns heatmap plot with the matplotlib heatmap in method description. * Removed wget. * Fixed links. Moved model sanity check to constructor. Removed panadas installation. Updated tests. * Integrate sklearn pd functions. In progress... * Removed sklearn private methods * Refactored blackbox case. * Updated method page. * Minor clarifications. * Solved mypy issues. * Addressed minor comments. * Minor correction for error messages and comments conventions. * Fixed test from previous commit. * isort on utils/visualizations.py * Fixed deciles computation. * Fixed for binary classification. * Add process pd and ice for plotting. * Included warning for the length. * Removed auto options * Removed auto. Fixed tests and docs. * Minor corrections. * Revert to deciles on full dataset * Changed a few error messages. Included one test for unknown kind. * Improved error messages and included a warning for target_names * Removed blank lines. * Fixed tests. * Split inital implementation into PartialDependence and TreePartialDependence. * Fixed tests. * Isort and removed unnecessary fixture from conftest.py * Updated PD example. * Updated method description. * Removed uncessary classes and imports. * Minor doc updates. Minor sanity checks refactoring. * Improved docs for TreePartialDependence. * Included ABC for the base class and removed for the derived one. * Fixed deciles display * Improved plots by adding pd limits * Fixed min-max pd plots for share_y. * Improved plots: zoom in for num and cat plots, add decile ticks for num-cat, sharey num-cats, updated images. * Solved minor display bug in num-cat for deciles. * Updated linear regression plots. * Minor docstrings correction: pairs of features -> tuples of features. * Removed unnecessary argument in _compute_pd_limits and updated return docs for helper plotting functions. Co-authored-by: Ashley Scillitoe <ashley.scillitoe@seldon.io>
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Implementation of the partial dependence (PD) and individual conditional expectation (ICE) leveraging
sklearnimplementation.Some functionalities that it includes
sklearnestimators)TODOs: