Auto-WEKA

Auto-WEKA considers the problem of simultaneously selecting a learning algorithm and setting its hyperparameters, going beyond previous methods that address these issues in isolation. Auto-WEKA does this using a fully automated approach, leveraging recent innovations in Bayesian optimization. Our hope is that Auto-WEKA will help non-expert users to more effectively identify machine learning algorithms and hyperparameter settings appropriate to their applications, and hence to achieve improved performance.

homepage: http://www.cs.ubc.ca/labs/beta/Projects/autoweka/

version	versionsuffix	toolchain
2.6	-WEKA-3.8.5-Java-11	system

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