2020 is over. Time to look back at the amazing major features we introduced to Auto-Sklearn.
Since our initial release of auto-sklearn 0.0.1 in May 2016 and the publication of the NeurIPS paper “Efficient and Robust Automated Machine Learning” in 2015, we have spent a lot of time on maintaining, refactoring and improving code, but also on new research. Now, we’re finally ready to share the next version of our flagship AutoML system: Auto-Sklearn 2.0.
This new version is based on our experience from winning the second ChaLearn AutoML challenge@PAKDD’18 (see also the respective chapter in the AutoML book) and integrates improvements we thoroughly studied in our upcoming paper. Here are the main insights:
Our ML Freiburg lab is the world champion in automatic machine learning (AutoML) again! After winning the first international AutoML challenge (2015-2016), we also just won the second international AutoML challenge (2017-2018). Our system PoSH-Auto-sklearn outperformed all other 41 participating AutoML systems. (more…)