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Large scale biomedical data analysis with tree-based automated machine learning

Published:08 July 2020Publication History

ABSTRACT

Tree-based Pipeline Optimization Tool (TPOT) is an automated machine learning (AutoML) system that recommends optimal pipeline for supervised learning problems by scanning data for novel features, selecting appropriate models and optimizing their parameters. However, like other AutoML systems, TPOT may reach computational resource limits when working on big data such as whole-genome expression data. We develop two novel features for TPOT, Feature Set Selector and Template, which leverage domain knowledge, greatly reduce the computational expense and flexibly extend TPOT's application to biomedical big data analysis.

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References

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    • Published in

      cover image ACM Conferences
      GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
      July 2020
      1982 pages
      ISBN:9781450371278
      DOI:10.1145/3377929

      Copyright © 2020 Owner/Author

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      Association for Computing Machinery

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      Publication History

      • Published: 8 July 2020

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