format_y

Formats response variable based on the ml-type variable passed by the config file.
For regression analyses the response variable will be explicitly transformed to type numeric.
For Classification experiments the response variable will be explicitly transformed to a factor.
Time-to-event models are to be implemented in the near future.

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. 

format_y function

<dl><dt>y</dt>
<dd>vector of response varibale.</dd>
<dt>ml.type</dt>
<dd>type of experiment (chracater).</dd></dl>

Arguments

Author

format_y — format_y

<dl>

<dt>y</dt>
<dd>vector of response varibale.</dd>


<dt>ml.type</dt>
<dd>type of experiment (chracater).</dd>

</dl>

format_y: format_y

Description

Usage

Value

Arguments

Author