create_resample_experiment

Creates an object of a resampling experiment.

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' <https://github.com/topepo/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' <https://www.nextflow.io/>) and hereby improve scalability,
standardization, and re-producibility in the context of machine-learning.

Sebastian Malkusch

flowml

A Backend for a 'nextflow' Pipeline that Performs
Machine-Learning-Based Modeling of Biomedical Data

Kolja Becker

Alexander Peltzer

Neslihan Kaya

Boehringer Ingelheim Ltd. 

create_resample_experiment function

<dl><dt>seed</dt>
<dd>sets the seed for the random number generator to guarantee reproducibility.
(int)</dd>
<dt>data_df</dt>
<dd>data frame to be learned from.
(tibble::tibble)</dd>
<dt>parser_inst</dt>
<dd>instance of parser object. (optparse::parse_args).</dd>
<dt>model_inst</dt>
<dd>instance of caret_train object (caret::train).</dd>
<dt>config_inst</dt>
<dd>list of config options (list).</dd>
<dt>n_features</dt>
<dd>number of features (int).</dd></dl>

Arguments

Author

create_resample_experiment — create_resample_experiment

<dl>

<dt>seed</dt>
<dd>sets the seed for the random number generator to guarantee reproducibility.
(int)</dd>


<dt>data_df</dt>
<dd>data frame to be learned from.
(tibble::tibble)</dd>


<dt>parser_inst</dt>
<dd>instance of parser object. (optparse::parse_args).</dd>


<dt>model_inst</dt>
<dd>instance of caret_train object (caret::train).</dd>


<dt>config_inst</dt>
<dd>list of config options (list).</dd>


<dt>n_features</dt>
<dd>number of features (int).</dd>

</dl>

create_resample_experiment: create_resample_experiment

Description

Usage

Value

Arguments

Author

Details