From 52437dd139bc8f020ed7254578116d6e63f38519 Mon Sep 17 00:00:00 2001 From: Chitu Okoli Date: Mon, 5 Feb 2024 04:10:46 +0100 Subject: [PATCH] Tried to correct documentation of ale() versus ale-package --- R/ale-package.R | 1 - R/ale_core.R | 4 ---- man/ale-package.Rd | 41 +++++++++++++++++++++++++++++++++++++++++ man/ale.Rd | 44 ++------------------------------------------ 4 files changed, 43 insertions(+), 47 deletions(-) create mode 100644 man/ale-package.Rd diff --git a/R/ale-package.R b/R/ale-package.R index d5bd7db..d406ce4 100644 --- a/R/ale-package.R +++ b/R/ale-package.R @@ -18,7 +18,6 @@ #' #' @author Chitu Okoli \email{Chitu.Okoli@skema.edu} #' @docType package -#' @name ale #' #' @import dplyr #' @import purrr diff --git a/R/ale_core.R b/R/ale_core.R index 082f388..4c68a40 100644 --- a/R/ale_core.R +++ b/R/ale_core.R @@ -85,10 +85,6 @@ #' #' #' -#' @section About the `{ale}` package: -#' Overview of the `{ale}` package. -#' -#' #' @export #' #' @references Okoli, Chitu. 2023. diff --git a/man/ale-package.Rd b/man/ale-package.Rd new file mode 100644 index 0000000..c05783a --- /dev/null +++ b/man/ale-package.Rd @@ -0,0 +1,41 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/ale-package.R +\docType{package} +\name{ale-package} +\alias{ale-package} +\title{Interpretable Machine Learning and Statistical Inference with Accumulated Local Effects (ALE)} +\description{ +Accumulated Local Effects (ALE) were initially developed as a model-agnostic +approach for global explanations of the results of black-box machine learning +algorithms. ALE has a key advantage over other approaches like partial +dependency plots (PDP) and SHapley Additive exPlanations (SHAP): its values +represent a clean functional decomposition of the model. As such, ALE values +are not affected by the presence or absence of interactions among variables +in a mode. Moreover, its computation is relatively rapid. This package +rewrites the original code from the \href{https://CRAN.r-project.org/package=ALEPlot}{\code{{ALEPlot}} package} +for calculating ALE data +and it completely reimplements the plotting of ALE values. It also extends +the original ALE concept to add bootstrap-based confidence intervals and +ALE-based statistics that can be used for statistical inference. +For more details, see Okoli, Chitu. 2023. “Statistical Inference Using +Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” +arXiv. \url{https://arxiv.org/abs/2310.09877}. +} +\references{ +Okoli, Chitu. 2023. +“Statistical Inference Using Machine Learning and Classical Techniques Based +on Accumulated Local Effects (ALE).” arXiv. \url{https://arxiv.org/abs/2310.09877}. +} +\seealso{ +Useful links: +\itemize{ + \item \url{https://github.com/Tripartio/ale} + \item \url{https://tripartio.github.io/ale/} + \item Report bugs at \url{https://github.com/Tripartio/ale/issues} +} + +} +\author{ +Chitu Okoli \email{Chitu.Okoli@skema.edu} +} +\keyword{internal} diff --git a/man/ale.Rd b/man/ale.Rd index ab52bc9..5ec960c 100644 --- a/man/ale.Rd +++ b/man/ale.Rd @@ -1,10 +1,8 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ale-package.R, R/ale_core.R -\docType{package} +% Please edit documentation in R/ale_core.R \name{ale} \alias{ale} -\alias{ale-package} -\title{Interpretable Machine Learning and Statistical Inference with Accumulated Local Effects (ALE)} +\title{Create and return ALE data, statistics, and plots} \usage{ ale( data, @@ -252,22 +250,6 @@ arguments to understand how these are determined. } } \description{ -Accumulated Local Effects (ALE) were initially developed as a model-agnostic -approach for global explanations of the results of black-box machine learning -algorithms. ALE has a key advantage over other approaches like partial -dependency plots (PDP) and SHapley Additive exPlanations (SHAP): its values -represent a clean functional decomposition of the model. As such, ALE values -are not affected by the presence or absence of interactions among variables -in a mode. Moreover, its computation is relatively rapid. This package -rewrites the original code from the \href{https://CRAN.r-project.org/package=ALEPlot}{\code{{ALEPlot}} package} -for calculating ALE data -and it completely reimplements the plotting of ALE values. It also extends -the original ALE concept to add bootstrap-based confidence intervals and -ALE-based statistics that can be used for statistical inference. -For more details, see Okoli, Chitu. 2023. “Statistical Inference Using -Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” -arXiv. \url{https://arxiv.org/abs/2310.09877}. - \code{ale()} is the central function that manages the creation of ALE data and plots for one-way ALE. For two-way interactions, see \code{\link[=ale_ixn]{ale_ixn()}}. This function calls \code{ale_core} (a non-exported function) that manages the ALE data and plot creation in detail. For details, see @@ -356,11 +338,6 @@ For more details on formatting progress bars to your liking, see the introductio to the \href{https://progressr.futureverse.org/articles/progressr-intro.html}{\code{{progressr}} package}. } -\section{About the \code{{ale}} package}{ - -Overview of the \code{{ale}} package. -} - \examples{ diamonds set.seed(0) @@ -437,21 +414,4 @@ gridExtra::grid.arrange(grobs = ale_gam_diamonds_custom$plots, ncol = 2) Okoli, Chitu. 2023. “Statistical Inference Using Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” arXiv. \url{https://arxiv.org/abs/2310.09877}. - -Okoli, Chitu. 2023. -“Statistical Inference Using Machine Learning and Classical Techniques Based -on Accumulated Local Effects (ALE).” arXiv. \url{https://arxiv.org/abs/2310.09877}. -} -\seealso{ -Useful links: -\itemize{ - \item \url{https://github.com/Tripartio/ale} - \item \url{https://tripartio.github.io/ale/} - \item Report bugs at \url{https://github.com/Tripartio/ale/issues} -} - -} -\author{ -Chitu Okoli \email{Chitu.Okoli@skema.edu} } -\keyword{internal}