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:E. F. Haghish [aut, cre, cph]

autoEnsemble_0.3.tar.gz
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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'))

Peer review:

Bug tracker:https://github.com/haghish/autoensemble/issues

On CRAN:

aialgorithmautomated-machine-learningautomlautoml-algorithmsensembleensemble-learningh2oh2oaimachine-learningmachinelearningmetalearningstack-ensemblestacked-ensemblesstacking

4.32 score 5 stars 21 scripts 204 downloads 5 exports 7 dependencies

Last updated 4 months agofrom:86fadc8b26. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 28 2024
R-4.5-winWARNINGOct 28 2024
R-4.5-linuxWARNINGOct 28 2024
R-4.4-winWARNINGOct 28 2024
R-4.4-macWARNINGOct 28 2024
R-4.3-winWARNINGOct 28 2024
R-4.3-macWARNINGOct 28 2024

Exports:autoEnsembleensembleevaluateh2o.get_idsmodelSelection

Dependencies:bitopsbootcurlh2oh2otoolsjsonliteRCurl