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EEML  

Ensemble Explainable Machine Learning Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("EEML", "0.1.1")



Attach the package and use:
library("EEML")
Maintained by
Dr. Ranjit Kumar Paul
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-07-14
Latest Update: 2024-07-14
Description:
We introduced a novel ensemble-based explainable machine learning model using Model Confidence Set (MCS) and two stage Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The model combined the predictive capabilities of different machine-learning models and integrates the interpretability of explainability methods. To develop the proposed algorithm, a two-stage Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) framework was employed. The package has been developed using the algorithm of Paul et al. <doi:10.1007/s40009-023-01218-x> and Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>.
How to cite:
Dr. Ranjit Kumar Paul (2024). EEML: Ensemble Explainable Machine Learning Models. R package version 0.1.1, https://cran.r-project.org/web/packages/EEML. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2024-07-14 14:50)
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Complete documentation for EEML
Functions, R codes and Examples using the EEML R package
Full EEML package functions and examples
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