gaussian_kernel

explained_instance

simulated_instance

<p>LIME kernel from the original article with sigma = 1.</p>

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>.

Mateusz Staniak

live

Local Interpretable (Model-Agnostic) Visual Explanations

Przemys<c5><82>aw Biecek

gaussian_kernel function

LIME kernel from the original article with sigma = 1. — gaussian_kernel

LIME kernel from the original article with sigma = 1.

gaussian_kernel: LIME kernel from the original article with sigma = 1.

Description

Usage

Arguments

Value