.prepare_familiar_data_sets

Information concerning models, features and the experiment is
processed and stored in familiarData objects. Information can be extracted
from these objects as csv files, or by plotting, or multiple objects can be
combined into familiarCollection objects, which allows aggregated exports.

internal

Single unified interface for end-to-end modelling of regression,
categorical and time-to-event (survival) outcomes. Models created using
familiar are self-containing, and their use does not require additional
information such as baseline survival, feature clustering, or feature
transformation and normalisation parameters. Model performance,
calibration, risk group stratification, (permutation) variable importance,
individual conditional expectation, partial dependence, and more, are
assessed automatically as part of the evaluation process and exported in
tabular format and plotted, and may also be computed manually using export
and plot functions. Where possible, metrics and values obtained during the
evaluation process come with confidence intervals.

Alex Zwanenburg

familiar

End-to-End Automated Machine Learning and Model Evaluation

Steffen Löck

Stefan Leger

Iram Shahzadi

Asier Rabasco Meneghetti

Sebastian Starke

Technische Universität Dresden 

German Cancer Research Center (DKFZ) 

.prepare_familiar_data_sets function

<dl><dt>cl</dt>
<dd>Cluster for parallel processing.</dd>
<dt>only_pooling</dt>
<dd>Flag that, if set, forces evaluation of only the
top-level data, and not e.g. ensembles.</dd>
<dt>message_indent</dt>
<dd>indent that messages should have.</dd>
<dt>verbose</dt>
<dd>Sets verbosity</dd></dl>

Arguments

Prepare familiarData objects for evaluation at runtime. — .prepare_familiar_data_sets

<dl>

<dt>cl</dt>
<dd>Cluster for parallel processing.</dd>


<dt>only_pooling</dt>
<dd>Flag that, if set, forces evaluation of only the
top-level data, and not e.g. ensembles.</dd>


<dt>message_indent</dt>
<dd>indent that messages should have.</dd>


<dt>verbose</dt>
<dd>Sets verbosity</dd>

</dl>

Prepare familiarData objects for evaluation at runtime.

.prepare_familiar_data_sets: Prepare familiarData objects for evaluation at runtime.

Description

Usage

Value

Arguments

Details