EpistasisLab/tpot: TPOT now supports integration with Dask for parallelization
- Randy Olson
- Weixuan Fu
- Daniel
- Nathan
- PGijsbers
- Grishma Jena
- Tom Augspurger
- PRONOjit Saha
- Sebastian Raschka
- sahilshah1194
- sohnam
- DanKoretsky
- kadarakos
- Geoffrey Bradway
- bartdp1
- Jose Ortiz
- Michal Ficek
- Akshay Varik
- Ted
- screwed99
- Matt Ritter
- kamalasaurus
- Randy Carnevale
- Matthew Rocklin
- Hristo
- iddober
- Francis T. O'Donovan
- Erin LeDell
- Alex Fortin
- Adithya Balaji
Publication date
September 2018
DOIAbstract
TPOT now supports integration with Dask for parallelization + smart caching. Big thanks to the Dask dev team for making this happen! Add supports for imputation/sparse matrices into predict and predict_proba functions. TPOTClassifier and TPOTRegressor now follows scikit-learn estimator API. Refining scoring parameter in TPOT API for accepting Scorer object. Refine parameters in VarianceThreshold and FeatureAgglomeration. Improve documentation Add supports of using memory caching within a Pipeline via a optional memory parameter
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