D.3: Auto-Weka

• Short Description:

Tool that performs combined algorithm selection and hyperparameter optimization over the classification and regression algorithms implements in WEKA. Auto-WEKA explores hyperparameter settings for a number of algorithms and recommends to a user which method will likely have good generalization performance, using model-based optimization techniques.

• Reference, URL: https://www.cs.ubc.ca/labs/algorithms/Projects/autoweka/

• Applicable Business Category: All/Smart Industry

• Application in relevant Projects/Initiatives:

• Asset Type: Executable, Platform

• AI Breadth: ML

• Learning Ability: Supervised & Unsupervised learning

• Related technologies: Automated Machine Learning (AutoML), WEKA, Bayesian Optimisation

• Applicable Research Area: Verifiable AI

• Applicable Technical Category: Machine Learning

• License Information: GNU General Public License version 3

• Related to circularity and sustainability: Not directly

• Audience: Developers

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