AutoML Benchmark (AMLB)
AutoML frameworks compared on classification accuracy and ROC AUC across a shared set of OpenML tasks.
Results of the AutoML Benchmark (AMLB), which ran automated machine-learning frameworks on a shared set of classification tasks and published the evaluations on OpenML as study 226 (www.openml.org/s/226, 2019). Each target is one framework; each run is one dataset, with the predictive accuracy and ROC AUC recorded there (0-1, higher is better).
Metrics
- predictive_accuracy
- area_under_roc_curve
Targets (6)
- autosklearn
- autoweka
- h2oautoml
- randomforest
- tpot
- tunedrandomforest
Published by OpenML.
Metrics
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