predict_pro

A unified S3 generic method to generate prognostic risk scores from
various trained model objects. This decouples the prediction implementation
from the high-level evaluation logic, facilitating extensibility.

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

predict_pro function

<dl><dt>object</dt>
<dd>A trained model object with class <code>pro_model</code>.</dd>
<dt>newdata</dt>
<dd>A data frame containing features for prediction.</dd>
<dt>...</dt>
<dd>Additional arguments passed to specific methods.</dd></dl>

Arguments

Generic Prediction Interface for Prognostic Models — predict_pro

<dl>

<dt>object</dt>
<dd>A trained model object with class <code>pro_model</code>.</dd>


<dt>newdata</dt>
<dd>A data frame containing features for prediction.</dd>


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

</dl>

predict_pro: Generic Prediction Interface for Prognostic Models

Description

Usage

Value

Arguments