.update_initial_settings

This function updates and checks parameters related to data set parsing based
on the available data set.

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_initial_settings function

<dl><dt>formula</dt>
<dd>User-provided formula, may be absent (<code>NULL</code>).</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.</dd>
<dt>check_stringency</dt>
<dd>Specifies stringency of various checks. This is mostly:<ul>
<li><code>strict</code>: default value used for <code>summon_familiar</code>. Thoroughly checks
input data. Used internally for checking development data.</li>
<li><code>external_warn</code>: value used for <code>extract_data</code> and related methods. Less
stringent checks, but will warn for possible issues. Used internally for
checking data for evaluation and explanation.</li>
<li><code>external</code>: value used for external methods such as <code>predict</code>. Less
stringent checks, particularly for identifier and outcome columns, which may
be completely absent. Used internally for <code>predict</code>.</li>
</ul></dd></dl>

Arguments

Internal check and update of settings related to data set parsing — .update_initial_settings

<dl>

<dt>formula</dt>
<dd>User-provided formula, may be absent (<code>NULL</code>).</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.</dd>


<dt>check_stringency</dt>
<dd>Specifies stringency of various checks. This is mostly:<ul>
<li><code>strict</code>: default value used for <code>summon_familiar</code>. Thoroughly checks
input data. Used internally for checking development data.</li>
<li><code>external_warn</code>: value used for <code>extract_data</code> and related methods. Less
stringent checks, but will warn for possible issues. Used internally for
checking data for evaluation and explanation.</li>
<li><code>external</code>: value used for external methods such as <code>predict</code>. Less
stringent checks, particularly for identifier and outcome columns, which may
be completely absent. Used internally for <code>predict</code>.</li>
</ul></dd>

</dl>

Internal check and update of settings related to data set parsing

.update_initial_settings: Internal check and update of settings related to data set parsing

Description

Usage

Value

Arguments