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Analysis of Open-Source Hyperparameter Optimization Software Trends

  • Lee, Yo-Seob (School of ICT Convergence, Pyeongtaek University) ;
  • Moon, Phil-Joo (Dept. of Information & Communication, Pyeongtaek University)
  • Received : 2019.09.26
  • Accepted : 2019.10.28
  • Published : 2019.12.31

Abstract

Recently, research using artificial neural networks has further expanded the field of neural network optimization and automatic structuring from improving inference accuracy. The performance of the machine learning algorithm depends on how the hyperparameters are configured. Open-source hyperparameter optimization software can be an important step forward in improving the performance of machine learning algorithms. In this paper, we review open-source hyperparameter optimization softwares.

References

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