Automated machine learning system
Auto-WEKA is an automated machine learning system based on Weka by Chris Thornton, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown.[1] An extended version was published as Auto-WEKA 2.0.[2] Auto-WEKA was named the first prominent AutoML system in a neutral comparison study.[3]
It received the test-of-time award of the SIGKDD conference in 2023.[4]
- ^ Thornton, Chris; Hutter, Frank; Hoos, Holger H.; Leyton-Brown, Kevin (August 11, 2013). "Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms". Association for Computing Machinery. pp. 847–855. doi:10.1145/2487575.2487629 – via ACM Digital Library.
- ^ Kotthoff, Lars; Thornton, Chris; Hoos, Holger H.; Hutter, Frank; Leyton-Brown, Kevin (August 12, 2017). "Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA". Journal of Machine Learning Research. 18 (25): 1–5 – via jmlr.org.
- ^ Gijsbers, Pieter; Bueno, Marcos L. P. (2024). "AMLB: an AutoML Benchmark". Journal of Machine Learning Research. 25: 6. arXiv:2207.12560.
- ^ "KDD 2023 - Awards". kdd.org.