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Using Bayesian optimization to effectively tune random forest and XGBoost hyperparameters for early Alzheimer's disease diagnosis

Fast facts

  • Internal authorship

    Louise Bloch, M.Sc.

  • Further publishers

    • Louise Bloch

  • Publishment

    • 2021

  • Anthology

    Using Bayesian optimization to effectively tune random forest and XGBoost hyperparameters for early Alzheimer's disease diagnosis

  • Organizational unit

    Computer science

  • Subjects

    • Computer science in general

  • Publication format

    Anthology contribution (Article)

Quote

Bloch, Louise & Friedrich, Christoph M. 2021. Using Bayesian optimization to effectively tune random forest and XGBoost hyperparameters for early Alzheimer's disease diagnosis. In Wireless Mobile Communication and Healthcare : 9th EAI International Conference, MobiHealth 2020, Virtual Event, November 19, 2020, Proceedings. Cham: Springer International Publishing, 285-299.

Notes and references

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