apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters

March 10, 2015 · Entered Twilight · 🏛 arXiv.org

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Repo contents: .gitignore, License.txt, README.md, code, diagrams, documentation, paper.pdf, slides.pdf

Authors Frederik Diehl, Andreas Jauch arXiv ID 1503.02946 Category cs.LG: Machine Learning Citations 1 Venue arXiv.org Repository https://github.com/FrederikDiehl/apsis ⭐ 25 Last Checked 2 months ago

Abstract

The apsis toolkit presented in this paper provides a flexible framework for hyperparameter optimization and includes both random search and a bayesian optimizer. It is implemented in Python and its architecture features adaptability to any desired machine learning code. It can easily be used with common Python ML frameworks such as scikit-learn. Published under the MIT License other researchers are heavily encouraged to check out the code, contribute or raise any suggestions. The code can be found at github.com/FrederikDiehl/apsis.