ShapleyOutlier (version 0.1.2)

Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances

Description

Based on Shapley values to explain multivariate outlyingness and to detect and impute cellwise outliers. Includes implementations of methods described in Mayrhofer and Filzmoser (2023) .

Copy Link

Version

Install

install.packages('ShapleyOutlier')

Monthly Downloads

199

Version

0.1.2

License

GPL-3

Maintainer

Marcus Mayrhofer

Last Published

October 17th, 2024

Functions in ShapleyOutlier (0.1.2)

new_shapley_interaction

Class constructor for class shapley_interaction.

%>%

Pipe operator

SCD

Detecting cellwise outliers using Shapley values.

plot.shapley_algorithm

Barplot and tileplot of Shapley values.

new_shapley_algorithm

Class constructor for class shapley_algorithm.

MOE

Detecting cellwise outliers using Shapley values based on local outlyingness.

plot.shapley

Barplot of Shapley values

new_shapley

Class constructor for class shapley.

plot.shapley_interaction

Plot of Shapley interaction indices

shapley_interaction

Decomposition of squared Mahalanobis distance using Shapley interaction indices.

print.shapley_algorithm

Print function for class shapley_algorithm.

print.shapley

Print function for class shapley.

print.shapley_interaction

Print function for class shapley_interaction.

shapley

Decomposition of squared Mahalanobis distance using Shapley values.

ShapleyOutlier-package

ShapleyOutlier: Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances

WeatherVienna

Weather data from Vienna