predict

predict.SCE

predict.SCA

Make predictions on new data using SCE or SCA models.

Implementation of Stepwise Clustered Ensemble (SCE) and Stepwise Cluster Analysis (SCA) for multivariate data analysis. The package provides comprehensive tools for feature selection, model training, prediction, and evaluation in hydrological and environmental modeling applications. Key functionalities include recursive feature elimination (RFE), Wilks feature importance analysis, model validation through out-of-bag (OOB) validation, and ensemble prediction capabilities. The package supports both single and multivariate response variables, making it suitable for complex environmental modeling scenarios. For more details see Li et al. (2021) <doi:10.5194/hess-25-4947-2021>.

Kailong Li

Stepwise Clustered Ensemble

predict function

<dl> <dt>object</dt>
<dd>An SCE or SCA model object</dd> <dt>newdata</dt>
<dd>New data for prediction</dd> <dt>...</dt>
<dd>Additional arguments</dd></dl>

Arguments

Predict Using SCE and SCA Models — predict

<dl>

 <dt>object</dt>
<dd>An SCE or SCA model object</dd>

 <dt>newdata</dt>
<dd>New data for prediction</dd>

 <dt>...</dt>
<dd>Additional arguments</dd>

</dl>

predict: Predict Using SCE and SCA Models

Description

Usage

Value

Arguments

See Also