predict_survival

predict_survival.fastml_native_survival

predict_survival.workflow

predict_survival.default

Predict survival probabilities from a survival model

Provides a guarded resampling workflow for training and evaluating machine-learning models.
When the guarded resampling path is used, preprocessing and model fitting are re-estimated within
each resampling split to reduce leakage risk. Supports multiple resampling schemes, integrates
with established engines in the 'tidymodels' ecosystem, and aims to improve evaluation reliability by
coordinating preprocessing, fitting, and evaluation within supported workflows. Offers a lightweight
AutoML-style workflow by automating model training, resampling, and tuning across multiple algorithms,
while keeping evaluation design explicit and user-controlled.

Selcuk Korkmaz

fastml

Guarded Resampling Workflows for Safe and Automated Machine
Learning in R

Dincer Goksuluk

Eda Karaismailoglu

predict_survival function

<dl><dt>fit</dt>
<dd>A fitted survival model.</dd>
<dt>newdata</dt>
<dd>A data frame of predictors for which to compute survival curves.</dd>
<dt>times</dt>
<dd>Numeric vector of evaluation times.</dd>
<dt>...</dt>
<dd>Additional arguments passed to methods.</dd></dl>

Arguments

Predict survival probabilities from a survival model — predict_survival

<dl>

<dt>fit</dt>
<dd>A fitted survival model.</dd>


<dt>newdata</dt>
<dd>A data frame of predictors for which to compute survival curves.</dd>


<dt>times</dt>
<dd>Numeric vector of evaluation times.</dd>


<dt>...</dt>
<dd>Additional arguments passed to methods.</dd>

</dl>

predict_survival: Predict survival probabilities from a survival model

Description

Usage

Value

Arguments