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IADT  

Interaction Difference Test for Prediction Models
View on CRAN: Click here


Download and install IADT package within the R console
Install from CRAN:
install.packages("IADT")

Install from Github:
library("remotes")
install_github("cran/IADT")

Install by package version:
library("remotes")
install_version("IADT", "1.2.1")



Attach the package and use:
library("IADT")
Maintained by
Thomas Welchowski
[Scholar Profile | Author Map]
First Published: 2023-07-13
Latest Update: 2023-07-13
Description:
Provides functions to conduct a model-agnostic asymptotic hypothesis test for the identification of interaction effects in black-box machine learning models. The null hypothesis assumes that a given set of covariates does not contribute to interaction effects in the prediction model. The test statistic is based on the difference of variances of partial dependence functions (Friedman (2008) and Welchowski (2022) ) with respect to the original black-box predictions and the predictions under the null hypothesis. The hypothesis test can be applied to any black-box prediction model, and the null hypothesis of the test can be flexibly specified according to the research question of interest. Furthermore, the test is computationally fast to apply as the null distribution does not require resampling or refitting black-box prediction models.
How to cite:
Thomas Welchowski (2023). IADT: Interaction Difference Test for Prediction Models. R package version 1.2.1, https://cran.r-project.org/web/packages/IADT. Accessed 23 Feb. 2025.
Previous versions and publish date:
1.0.0 (2023-07-13 16:10)
Other packages that cited IADT R package
View IADT citation profile
Other R packages that IADT depends, imports, suggests or enhances
Complete documentation for IADT
Functions, R codes and Examples using the IADT R package
Full IADT package functions and examples
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