# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "ensembleML" in publications use:'
type: software
license: MIT
title: 'ensembleML: Unified Interface for Ensemble Machine Learning Methods'
version: 0.2.5
abstract: 'Provides a clean, unified interface for training, predicting, and evaluating
  ensemble machine learning models including Random Forest, Gradient Boosting (''XGBoost''),
  ''AdaBoost'', and ''Bagging''. All algorithms share a consistent API: em_fit(),
  em_predict(), em_evaluate(), and em_tune(). Includes built-in cross-validation,
  feature importance, calibration diagnostics, partial dependence plots, and model
  comparison utilities. Methods: Breiman (2001) <https://doi.org/10.1023/A:1010933404324>;
  Chen and Guestrin (2016) <https://doi.org/10.1145/2939672.2939785>; Freund and Schapire
  (1997) <https://doi.org/10.1006/jcss.1997.1504>; Breiman (1996) <https://doi.org/10.1007/BF00058655>.'
authors:
- family-names: Islam
  given-names: Sadikul
  email: sadikul.islamiasri@gmail.com
  orcid: https://orcid.org/0000-0003-2924-7122
preferred-citation:
  type: manual
  title: 'ensembleML: Unified Interface for Ensemble Machine Learning Methods'
  authors:
  - family-names: Islam
    given-names: Sadikul
    email: sadikul.islamiasri@gmail.com
    orcid: https://orcid.org/0000-0003-2924-7122
  year: '2026'
  notes: R package version 0.2.0
  url: https://cran.r-project.org/package=ensembleML
repository: https://cran.r-universe.dev
commit: 3d5598315619093e1e3401ec629fa97f5da89bd8
date-released: '2026-05-20'
contact:
- family-names: Islam
  given-names: Sadikul
  email: sadikul.islamiasri@gmail.com
  orcid: https://orcid.org/0000-0003-2924-7122
references:
- type: article
  title: Random Forests
  authors:
  - family-names: Breiman
    given-names: Leo
  journal: Machine Learning
  year: '2001'
  volume: '45'
  issue: '1'
  doi: 10.1023/A:1010933404324
  start: '5'
  end: '32'
- type: conference-paper
  title: 'XGBoost: A Scalable Tree Boosting System'
  authors:
  - family-names: Chen
    given-names: Tianqi
  - family-names: Guestrin
    given-names: Carlos
  collection-title: Proceedings of the 22nd ACM SIGKDD International Conference on
    Knowledge Discovery and Data Mining
  collection-type: proceedings
  year: '2016'
  publisher:
    name: ACM
  doi: 10.1145/2939672.2939785
  start: '785'
  end: '794'
  conference:
    name: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge
      Discovery and Data Mining
- type: article
  title: A Decision-Theoretic Generalization of On-Line Learning and an Application
    to Boosting
  authors:
  - family-names: Freund
    given-names: Yoav
  - family-names: Schapire
    given-names: Robert E.
  journal: Journal of Computer and System Sciences
  year: '1997'
  volume: '55'
  issue: '1'
  doi: 10.1006/jcss.1997.1504
  start: '119'
  end: '139'
- type: article
  title: Bagging Predictors
  authors:
  - family-names: Breiman
    given-names: Leo
  journal: Machine Learning
  year: '1996'
  volume: '24'
  issue: '2'
  doi: 10.1007/BF00058655
  start: '123'
  end: '140'