print.survdnn

Pretty prints a fitted `survdnn` model. Displays the formula,
network architecture, training configuration, and final training loss.

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

print.survdnn function

<dl><dt>x</dt>
<dd>An object of class `"survdnn"`, returned by [survdnn()].</dd>
<dt>...</dt>
<dd>Ignored (for future compatibility).</dd></dl>

Arguments

Print a survdnn Model — print.survdnn

<dl>

<dt>x</dt>
<dd>An object of class `"survdnn"`, returned by [survdnn()].</dd>


<dt>...</dt>
<dd>Ignored (for future compatibility).</dd>

</dl>

print.survdnn: Print a survdnn Model

Description

Usage

Value

Arguments

Examples