forestry-labs/interpretability_sandbox: Model Distillation and Interpretability Methods for Machine Learning Models

Provides several methods for model distillation and interpretability for general black box machine learning models and treatment effect estimation methods. For details on the algorithms implemented, see <https://forestry-labs.github.io/distillML/index.html> Brian Cho, Theo F. Saarinen, Jasjeet S. Sekhon, Simon Walter.

Getting started

Package details

MaintainerTheo Saarinen <theo_s@berkeley.edu>
LicenseGPL (>=3)
Version0.1.0.14
URL https://github.com/forestry-labs/distillML
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("forestry-labs/interpretability_sandbox")
forestry-labs/interpretability_sandbox documentation built on April 26, 2023, 4:14 p.m.