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flowml
A Backend for a 'nextflow' Pipeline that Performs Machine-Learning-Based Modeling of Biomedical Data
View on CRAN: Click
here
Download and install flowml package within the R console
Install from CRAN:
install.packages("flowml")
Install from Github:
library("remotes")
install_github("cran/flowml") Install by package version:
library("remotes")
install_version("flowml", "0.1.3") Attach the package and use:
library("flowml")
Maintained by
Sebastian Malkusch
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.flowml . https://github.com/Boehringer-Ingelheim/flowml/issues . https://github.com/Boehringer-Ingelheim/flowml . flowml results . flowml.pdf . flowml_0.1.3.tar.gz . flowml_0.1.3.zip . flowml_0.1.3.zip . flowml_0.1.3.zip . flowml_0.1.3.tgz . flowml_0.1.3.tgz . flowml_0.1.3.tgz . flowml_0.1.3.tgz . flowml_0.1.3.tgz . flowml_0.1.3.tgz . flowml archive . https://CRAN.R-project.org/package=flowml .
First Published: 2023-10-09
Latest Update: 2024-02-16
Description:
Provides functionality to perform machine-learning-based modeling in a computation pipeline.
Its functions contain the basic steps of machine-learning-based knowledge discovery workflows,
including model training and optimization, model evaluation, and model testing.
To perform these tasks, the package builds heavily on existing machine-learning packages,
such as 'caret' and associated packages.
The package can train multiple models, optimize model hyperparameters by performing a grid search
or a random search, and evaluates model performance by different metrics.
Models can be validated either on a test data set, or in case of a small sample size
by k-fold cross validation or repeated bootstrapping.
It also allows for 0-Hypotheses generation by performing permutation experiments.
Additionally, it offers methods of model interpretation and item categorization
to identify the most informative features from a high dimensional data space.
The functions of this package can easily be integrated into computation pipelines
(e.g. 'nextflow' ) and hereby improve scalability,
standardization, and re-producibility in the context of machine-learning.
How to cite:
Sebastian Malkusch (2023). flowml: A Backend for a 'nextflow' Pipeline that Performs Machine-Learning-Based Modeling of Biomedical Data. R package version 0.1.3, https://cran.r-project.org/web/packages/flowml. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.2 (2023-10-09 14:50)
Other packages that cited flowml R package
View flowml citation profile
Other R packages that flowml depends,
imports, suggests or enhances
Complete documentation for flowml
Functions, R codes and Examples using
the flowml R package
Some associated functions: Resampler . create_parser . create_resample_experiment . fml_bootstrap . fml_example . fml_interpret . fml_train . fml_validate . format_y . run_abc_analysis .
Some associated R codes: fml_bootstrap.R . fml_categorize.R . fml_example.R . fml_format_response.R . fml_globals.R . fml_grids.R . fml_interpret.R . fml_parser.R . fml_resample.R . fml_resampler.R . fml_train.R . fml_validate.R . Full flowml package functions and examples
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