- Dr. Lars Kotthoff, Department of Computer Science, University of British Columbia
- 15 March 2017
Niels Bohrweg 1
2333 CA Leiden
Auto-WEKA: Automatic model selection and hyperparameter optimization in WEKA
Applying machine learning to practical problems requires selecting a machine learning approach from hundreds that are available. This is a difficult task even for experts. AutoML, the automatic selection of the best machine learning approach for a given problem, promises to make machine learning much more accessible to practitioners. In this talk, I will give an overview of Auto-WEKA, which intelligently chooses the best preprocessing method, learner, and parameterisation for given data. I will introduce the concepts that make it work and give a demonstration.
Dr. Lars Kotthoff is a postdoctoral fellow at the University of British Columbia. He previously held postdoctoral positions at University College Cork, Ireland, and the University of St Andrews, Scotland, where he also received his PhD. He has been awarded several governmental and industrial grants and fellowships for his research and won two best paper awards with his co-authors.