fmeffects: An R Package for Forward Marginal Effects
Machine Learning
2024-09-13 v2 Econometrics
Machine Learning
Abstract
Forward marginal effects have recently been introduced as a versatile and effective model-agnostic interpretation method particularly suited for non-linear and non-parametric prediction models. They provide comprehensible model explanations of the form: if we change feature values by a pre-specified step size, what is the change in the predicted outcome? We present the R package fmeffects, the first software implementation of the theory surrounding forward marginal effects. The relevant theoretical background, package functionality and handling, as well as the software design and options for future extensions are discussed in this paper.
Keywords
Cite
@article{arxiv.2310.02008,
title = {fmeffects: An R Package for Forward Marginal Effects},
author = {Holger Löwe and Christian A. Scholbeck and Christian Heumann and Bernd Bischl and Giuseppe Casalicchio},
journal= {arXiv preprint arXiv:2310.02008},
year = {2024}
}