From 469e2a3825dbd23b253d84490dfa3cd174c608a6 Mon Sep 17 00:00:00 2001 From: Sebastian Fischer Date: Tue, 9 Apr 2024 08:54:45 +0200 Subject: [PATCH] release 0.1.0 --- DESCRIPTION | 8 ++++---- man/mlr3fda-package.Rd | 10 ++++++++-- 2 files changed, 12 insertions(+), 6 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index d321d25..71dc2db 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -11,12 +11,13 @@ Authors@R: c( person("Bernd", "Bischl", , "bernd_bischl@gmx.net", role = "ctb", comment = c(ORCID = "0000-0001-6002-6980")) ) - Description: Extends the 'mlr3' ecosystem to functional analysis by adding support for irregular and regular functional data as defined in the 'tf' package. - The package provides 'PipeOp's for preprocessing functional columns and for + The package provides 'PipeOps' for preprocessing functional columns and for extracting scalar features, thereby allowing standard machine learning - algorithms to be applied afterwards. + algorithms to be applied afterwards. Available operations include simple + functional features such as the mean or maximum, smoothing, interpolation, + flattening, and functional 'PCA'. License: LGPL-3 URL: https://mlr3fda.mlr-org.com, https://github.com/mlr-org/mlr3fda BugReports: https://github.com/mlr-org/mlr3fda/issues @@ -35,7 +36,6 @@ Imports: Suggests: rpart, testthat (>= 3.0.0), - pracma, zoo Config/testthat/edition: 3 Encoding: UTF-8 diff --git a/man/mlr3fda-package.Rd b/man/mlr3fda-package.Rd index 8395a05..78b1431 100644 --- a/man/mlr3fda-package.Rd +++ b/man/mlr3fda-package.Rd @@ -4,9 +4,9 @@ \name{mlr3fda-package} \alias{mlr3fda} \alias{mlr3fda-package} -\title{mlr3fda: Extending 'mlr3' to functional data analysis} +\title{mlr3fda: Extending 'mlr3' to Functional Data Analysis} \description{ -Provides extensions for functional data analysis for 'mlr3'. +Extends the 'mlr3' ecosystem to functional analysis by adding support for irregular and regular functional data as defined in the 'tf' package. The package provides 'PipeOps' for preprocessing functional columns and for extracting scalar features, thereby allowing standard machine learning algorithms to be applied afterwards. Available operations include simple functional features such as the mean or maximum, smoothing, interpolation, flattening, and functional 'PCA'. } \section{Data types}{ @@ -41,4 +41,10 @@ Authors: \item Maximilian Muecke \email{muecke.maximilian@gmail.com} (\href{https://orcid.org/0009-0000-9432-9795}{ORCID}) } +Other contributors: +\itemize{ + \item Fabian Scheipl \email{fabian.scheipl@googlemail.com} (\href{https://orcid.org/0000-0001-8172-3603}{ORCID}) [contributor] + \item Bernd Bischl \email{bernd_bischl@gmx.net} (\href{https://orcid.org/0000-0001-6002-6980}{ORCID}) [contributor] +} + }