Package: autoEnsemble 0.3
autoEnsemble: Automated Stacked Ensemble Classifier for Severe Class Imbalance
An AutoML algorithm is developed to construct homogeneous or heterogeneous stacked ensemble models using specified base-learners. Various criteria are employed to identify optimal models, enhancing diversity among them and resulting in more robust stacked ensembles. The algorithm optimizes the model by incorporating an increasing number of top-performing models to create a diverse combination. Presently, only models from 'h2o.ai' are supported.
Authors:
autoEnsemble_0.3.tar.gz
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autoEnsemble_0.3.tgz(r-4.4-any)autoEnsemble_0.3.tgz(r-4.3-any)
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autoEnsemble.pdf |autoEnsemble.html✨
autoEnsemble/json (API)
# Install 'autoEnsemble' in R: |
install.packages('autoEnsemble', repos = c('https://haghish.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/haghish/autoensemble/issues
aialgorithmautomated-machine-learningautomlautoml-algorithmsensembleensemble-learningh2oh2oaimachine-learningmachinelearningmetalearningstack-ensemblestacked-ensemblesstacking
Last updated 4 months agofrom:86fadc8b26. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 28 2024 |
R-4.5-win | WARNING | Oct 28 2024 |
R-4.5-linux | WARNING | Oct 28 2024 |
R-4.4-win | WARNING | Oct 28 2024 |
R-4.4-mac | WARNING | Oct 28 2024 |
R-4.3-win | WARNING | Oct 28 2024 |
R-4.3-mac | WARNING | Oct 28 2024 |
Exports:autoEnsembleensembleevaluateh2o.get_idsmodelSelection
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Automatically Trains H2O Models and Builds a Stacked Ensemble Model | autoEnsemble |
Builds Stacked Ensemble Model from H2O Models | ensemble |
Evaluate H2O Model(s) Performance | evaluate |
h2o.get_ids | h2o.get_ids |
Selects Diverse Top-Performing Models for Stacking an Ensemble Model | modelSelection |
Stopping Criteria for Ending the Search | stopping_criteria |