.update_experimental_design_settings

This function checks which batches in the data set are assigned to model
development and external validation. Several errors may be raised if there
are inconsistencies such as an overlapping assignment, name mismatches etc.

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) 

.update_experimental_design_settings function

<dl><dt>section_table</dt>
<dd>data.table generated by the <code>extract_experimental_setup</code>
function. Contains information regarding the experiment.</dd>
<dt>data</dt>
<dd>Data set as loaded using the <code>.load_data</code> function.</dd>
<dt>settings</dt>
<dd>List of parameter settings for data set parsing and setting
up the experiment.</dd></dl>

Arguments

Internal function to check batch assignment to development and validation — .update_experimental_design_settings

<dl>

<dt>section_table</dt>
<dd>data.table generated by the <code>extract_experimental_setup</code>
function. Contains information regarding the experiment.</dd>


<dt>data</dt>
<dd>Data set as loaded using the <code>.load_data</code> function.</dd>


<dt>settings</dt>
<dd>List of parameter settings for data set parsing and setting
up the experiment.</dd>

</dl>

Internal function to check batch assignment to development and validation

.update_experimental_design_settings: Internal function to check batch assignment to development and validation

Description

Usage

Value

Arguments