EEML
Ensemble Explainable Machine Learning Models
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. (2023) doi:10.1007/s40009-023-01218-x and Yeasin and Paul (2024) doi:10.1007/s11227-023-05542-3.
- Version0.1.1
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Paul et al. (2023)
- Yeasin and Paul (2024)
- Last release08/01/2024
Team
Dr. Ranjit Kumar Paul
Dr. Md Yeasin
Show author detailsRolesAuthorDr. Dipanwita Haldar
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports3 packages