CRAN/E | processpredictR

processpredictR

Process Prediction

Installation

About

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 ways 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" .

Key Metrics

Version 0.1.0
R ≥ 2.10
Published 2023-01-17 466 days ago
Needs compilation? no
License MIT
License File
CRAN checks processpredictR results

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Maintainer

Maintainer

Gert Janssenswillen

gert.janssenswillen@uhasselt.be

Authors

Ivan Esin

aut

Gert Janssenswillen

cre

Hasselt University

cph

Material

README
Reference manual
Package source

Vignettes

Introduction to processpredictR: workflow

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 2.10

Imports

bupaR
edeaR
dplyr
forcats
magrittr
reticulate
tidyr
tidyselect
purrr
stringr
keras
tensorflow
rlang
data.table
mltools
ggplot2
cli
glue
plotly
progress

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