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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]
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 30 Apr. 2025.
Previous versions and publish date:
0.1.0 (2024-07-14 14:50)
Other packages that cited EEML R package
View EEML citation profile
Other R packages that EEML depends, imports, suggests or enhances
Complete documentation for EEML
Functions, R codes and Examples using the EEML R package
Full EEML package functions and examples
Downloads during the last 30 days
03/3104/0104/0204/0304/0404/0504/0604/0704/0804/0904/1004/1104/1204/1304/1404/1504/1604/1704/1804/1904/2004/2104/2204/2304/2404/2504/2604/2704/2804/29Downloads for EEML024681012141618202224TrendBars

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