Asynchronous Evolution of Data Mining Workflow Schemes by Strongly Typed Genetic Programming
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- @InProceedings{Pilat:2016:ICTAI,
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author = "Martin Pilat and Tomas Kren and Roman Neruda",
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booktitle = "2016 IEEE 28th International Conference on Tools with
Artificial Intelligence (ICTAI)",
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title = "Asynchronous Evolution of Data Mining Workflow Schemes
by Strongly Typed Genetic Programming",
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year = "2016",
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pages = "577--584",
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abstract = "This paper describes an algorithm for the automated
design of whole machine learning work-flows, including
preprocessing of the data and automatic creation of
several types of ensembles. The algorithm is based on
strongly typed genetic programming which ensures the
validity of the workflows. The evolution of the
individuals in the population is asynchronous in order
to improve the usage of computational resources. The
approach is validated on four data sets from the UCI
machine learning repository.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICTAI.2016.0094",
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month = nov,
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notes = "Also known as \cite{7814654}",
- }
Genetic Programming entries for
Martin Pilat
Tomas Kren
Roman Neruda
Citations