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Hyperparameter Tuning Approaches

  • Bartz-Beielstein T
  • Zaefferer M
Springer Nature Singapore, (2023), 71-119
DOI: 10.1007/978-981-19-5170-1_4
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Abstract

This chapter provides a broad overview over the different hyperparameter tunings. It details the process of HPT, and discusses popular HPT approaches and difficulties. It focuses on surrogate optimization, because this is the most powerful approach. It introduces...

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Bartz-Beielstein, T., & Zaefferer, M. (2023). Hyperparameter Tuning Approaches. In Hyperparameter Tuning for Machine and Deep Learning with R (pp. 71–119). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-5170-1_4

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