Data Mining Process Optimization in Computational Multi-agent Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00446456" target="_blank" >RIV/67985807:_____/15:00446456 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-20230-3_8" target="_blank" >http://dx.doi.org/10.1007/978-3-319-20230-3_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-20230-3_8" target="_blank" >10.1007/978-3-319-20230-3_8</a>

Result language
angličtina
Original language name
Data Mining Process Optimization in Computational Multi-agent Systems
Original language description
In this paper, we present an agent-based solution of metalearning problem which focuses on optimization of data mining processes. We exploit the framework of computational multi-agent systems in which various meta-learning problems have been already studied, e.g. parameter-space search or simple method recommendation. In this paper, we examine the effect of data preprocessing for machine learning problems. We perform the set of experiments in the search-space of data mining processes which is constituted by combinations of preprocessing methods with classifiers. The optimization takes place with respect to two criteria - error-rate and model learning time, which are partially complementary. The results of the consistent search algorithm on a number ofclassification data-sets are shown and the advantage of automated preprocessing augmentation of method recommendation is demonstrated.
Czech name
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Czech description
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Project
<a href="/en/project/LD13002" target="_blank" >LD13002: Modeling of complex systems for softcomputing methods</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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