SOTAVerified

apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters

2015-03-10Code Available0· sign in to hype

Frederik Diehl, Andreas Jauch

Code Available — Be the first to reproduce this paper.

Reproduce

Code

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.

Tasks

Reproductions