figure_pro

Generates and returns a ggplot object for Kaplan-Meier (KM)
survival curves or time-dependent ROC curves.

Provides a framework to build and evaluate diagnosis or
prognosis models using stacking, voting, and bagging ensemble
techniques with various base learners. The package also includes
tools for visualization and interpretation of models. The development
version of the package is available on 'GitHub' at
<https://github.com/xiaojie0519/E2E>. The methods
are based on the foundational work of Breiman (1996) <doi:10.1007/BF00058655>
on bagging and Wolpert (1992) <doi:10.1016/S0893-6080(05)80023-1>
on stacking.

Shanjie Luan

Ensemble Learning Framework for Diagnostic and Prognostic
Modeling

figure_pro function

<dl><dt>type</dt>
<dd>"km" or "tdroc"</dd>
<dt>data</dt>
<dd>list with:<ul>
<li>sample_score: data.frame(time, outcome, score)</li>
<li>evaluation_metrics: for "km" needs KM_Cutoff; for "tdroc" needs AUROC_Years
(numeric years like c(1,3,5), OR a named vector/list like c('1'=0.74,'3'=0.82,'5'=0.85))</li>
</ul></dd>
<dt>file</dt>
<dd>optional path to save</dd>
<dt>time_unit</dt>
<dd>"days" (default), "months", or "years" for df$time</dd></dl>

Arguments

Plot Prognostic Model Evaluation Figures — figure_pro

<dl>

<dt>type</dt>
<dd>"km" or "tdroc"</dd>


<dt>data</dt>
<dd>list with:<ul>
<li>sample_score: data.frame(time, outcome, score)</li>
<li>evaluation_metrics: for "km" needs KM_Cutoff; for "tdroc" needs AUROC_Years
(numeric years like c(1,3,5), OR a named vector/list like c('1'=0.74,'3'=0.82,'5'=0.85))</li>
</ul></dd>


<dt>file</dt>
<dd>optional path to save</dd>


<dt>time_unit</dt>
<dd>"days" (default), "months", or "years" for df$time</dd>

</dl>

figure_pro: Plot Prognostic Model Evaluation Figures

Description

Usage

Value

Arguments