Hybrid Multi-Agent System for Metalearning in Data Mining

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10284612" target="_blank" >RIV/00216208:11320/14:10284612 - isvavai.cz</a>

Result on the web

<a href="http://ceur-ws.org/Vol-1201/paper-13.pdf" target="_blank" >http://ceur-ws.org/Vol-1201/paper-13.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Hybrid Multi-Agent System for Metalearning in Data Mining

Original language description

In this paper, a multi-agent system for metalearning in the data mining domain is presented. The system provides a user with intelligent features, such as recommendation of suitable data mining techniques for a new dataset, parameter tuning of such techniques, and building up a metaknowledge base. The architecture of the system, together with different user scenarios, and the way they are handled by the system, are described.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2014

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

(2014) CEUR Workshop Proceedings

ISBN

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ISSN

1613-0073

e-ISSN

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Number of pages

2

Pages from-to

53-54

Publisher name

CEUR-WS

Place of publication

Neuveden

Event location

Praha

Event date

Aug 19, 2014

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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