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Model ingredients - model level feature effects and feature importance
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ingredients: Effects and Importances of Model Ingredients

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Collection of tools for assessment of feature importance and feature effects.

Key functions are:

  • feature_importance() for assessment of global level feature importance,
  • ceteris_paribus() for calculation of the Ceteris Paribus / What-If Profiles (read more at https://pbiecek.github.io/PM_VEE/ceterisParibus.html),
  • calculate_oscillations() for calculation of the Ceteris Paribus Oscillations (read more at https://pbiecek.github.io/PM_VEE/ceterisParibusOscillations.html),
  • ceteris_paribus_2d() for Ceteris Paribus 2D Profiles (read more at https://pbiecek.github.io/PM_VEE/ceterisParibus2d.html),
  • partial_dependency() for Partial Dependency Plots,
  • conditional_dependency() for Conditional Dependency Plots also called M Plots,
  • accumulated_dependency() for Accumulated Local Effects Plots,
  • aggregate_profiles() and cluster_profiles() for aggregation of Ceteris Paribus Profiles,
  • theme_drwhy() with a ggplot2 skin for all plots,
  • generic print() and plot() for better usability of selected explainers.

The package ingredients is a part of the DrWhy.AI universe.

Install

From GitHub

devtools::install_github("ModelOriented/ingredients")
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