evaluate_predictions_pro

Calculates performance metrics for external prediction sets.

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

evaluate_predictions_pro function

<dl><dt>prediction_df</dt>
<dd>Data frame with columns <code>time</code>, <code>outcome</code>, <code>score</code>, <code>ID</code>.</dd>
<dt>years_to_evaluate</dt>
<dd>Years for AUC.</dd></dl>

Arguments

Evaluate External Predictions — evaluate_predictions_pro

<dl>

<dt>prediction_df</dt>
<dd>Data frame with columns <code>time</code>, <code>outcome</code>, <code>score</code>, <code>ID</code>.</dd>


<dt>years_to_evaluate</dt>
<dd>Years for AUC.</dd>

</dl>

evaluate_predictions_pro: Evaluate External Predictions

Description

Usage

Value

Arguments