summarize_tune_survdnn

Aggregates cross-validation results from `tune_survdnn(return = "all")`
by configuration, metric, and optionally by time point.

Provides deep learning models for right-censored survival data using the 'torch' backend.
Supports multiple loss functions, including Cox partial likelihood, L2-penalized Cox, time-dependent Cox,
and accelerated failure time (AFT) loss. Offers a formula-based interface, built-in support for cross-validation,
hyperparameter tuning, survival curve plotting, and evaluation metrics such as the C-index, Brier score,
and integrated Brier score. For methodological details, see Kvamme et al. (2019) <https://www.jmlr.org/papers/v20/18-424.html>.

Imad El Badisy

survdnn

Deep Neural Networks for Survival Analysis Using 'torch'

Imad EL BADISY

summarize_tune_survdnn function

<dl><dt>tuning_results</dt>
<dd>The full tibble returned by `tune_survdnn(..., return = "all")`.</dd>
<dt>by_time</dt>
<dd>Logical; whether to group and summarize separately by time points.</dd></dl>

Arguments

Summarize survdnn Tuning Results — summarize_tune_survdnn

<dl>

<dt>tuning_results</dt>
<dd>The full tibble returned by `tune_survdnn(..., return = "all")`.</dd>


<dt>by_time</dt>
<dd>Logical; whether to group and summarize separately by time points.</dd>

</dl>

summarize_tune_survdnn: Summarize survdnn Tuning Results

Description

Usage

Value

Arguments