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SCE  

Stepwise Clustered Ensemble
View on CRAN: Click here


Download and install SCE package within the R console
Install from CRAN:
install.packages("SCE")

Install from Github:
library("remotes")
install_github("cran/SCE")

Install by package version:
library("remotes")
install_version("SCE", "1.1.4")



Attach the package and use:
library("SCE")
Maintained by
Kailong Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-06-23
Latest Update: 2025-07-25
Description:
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>.
How to cite:
Kailong Li (2025). SCE: Stepwise Clustered Ensemble. R package version 1.1.4, https://cran.r-project.org/web/packages/SCE. Accessed 04 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:24), 1.0.0 (2025-06-23 12:50), 1.1.0 (2025-07-02 09:00), 1.1.1 (2025-07-25 23:00), 1.1.2 (2025-10-05 00:10), 1.1.3 (2026-05-08 08:41)
Other packages that cited SCE R package
View SCE citation profile
Other R packages that SCE depends, imports, suggests or enhances
Complete documentation for SCE
Functions, R codes and Examples using the SCE R package
Full SCE package functions and examples
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