Description
Local Interpretable (Model-Agnostic) Visual Explanations.
Description
Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <doi:10.32614/RJ-2018-072>.
README.md
live: Local Interpretable (Model-agnostic) Visual Explanations
Installation
To get started, install stable CRAN version:
install.packages("live")
or the development version:
devtools::install_github("ModelOriented/live")
Features coming up next:
better support for comparing explanations for different models / different instances,
improved Shiny application (see
live_shinyfunction in development version).
If you have any bug reports, feature requests or ideas to improve the methodology, feel free to leave an issue.
Materials
Find the paper about live and breakDown in R Journal.
Website: https://mi2datalab.github.io/live/
Conference talks on live: Wrocław 2018, Berlin 2017.
Python implementation of LIME and info about the method: https://github.com/marcotcr/lime.