Asynchronous Evolution of Data Mining Workflow Schemes by Strongly Typed Genetic Programming

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00472406" target="_blank" >RIV/67985807:_____/16:00472406 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICTAI.2016.0094" target="_blank" >http://dx.doi.org/10.1109/ICTAI.2016.0094</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICTAI.2016.0094" target="_blank" >10.1109/ICTAI.2016.0094</a>

Result language
angličtina
Original language name
Asynchronous Evolution of Data Mining Workflow Schemes by Strongly Typed Genetic Programming
Original language description
This paper describes an algorithm for the automated design of whole machine learning workflows, 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 utilization of computational resources. The approach is validated on four data sets from the UCI machine learning repository.
Czech name
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Czech description
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Project
<a href="/en/project/GA15-19877S" target="_blank" >GA15-19877S: Automated Knowledge and Plan Modeling for Autonomous Robots</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 28th IEEE International Conference on Tools with Artificial Intelligence
ISBN
978-1-5090-4459-7
ISSN
2375-0197
e-ISSN
—
Number of pages
8
Pages from-to
577-584
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
San Jose
Event date
Nov 6, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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