Package: processpredictR
Type: Package
Title: Process Prediction
Version: 0.1.1
Authors@R: c(person("Ivan","Esin", email = "ivan.esin@student.uhasselt", role ="aut"),
      person("Gert","Janssenswillen", email = "gert.janssenswillen@uhasselt.be", role = "cre"),
      person("Hasselt University", role = "cph"))
Description: Means to predict process flow, such as process outcome, next activity, next time, remaining time, and remaining trace. Off-the-shelf predictive models based on the concept of Transformers are provided, as well as multiple way to customize the models. This package is partly based on work described in Zaharah A. Bukhsh, Aaqib Saeed, & Remco M. Dijkman. (2021). "ProcessTransformer: Predictive Business Process Monitoring with Transformer Network" <doi:10.48550/arXiv.2104.00721>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: bupaR, edeaR, eventdataR, dplyr, forcats, magrittr,
        reticulate, tidyr, tidyselect, purrr, stringr, keras,
        tensorflow, rlang, data.table, mltools, ggplot2, cli, glue,
        plotly
Config/testthat/edition: 3
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, lubridate
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-15 13:25:16 UTC; lucp8407
Author: Ivan Esin [aut],
  Gert Janssenswillen [cre],
  Hasselt University [cph]
Maintainer: Gert Janssenswillen <gert.janssenswillen@uhasselt.be>
Repository: CRAN
Date/Publication: 2025-09-15 14:00:02 UTC
Built: R 4.6.0; ; 2026-04-30 15:21:47 UTC; unix
