Data mining by symbolic fuzzy classifiers and genetic programming- state of the art and prospective approaches

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088873" target="_blank" >RIV/61989100:27240/13:86088873 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/13:86088873
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Data mining by symbolic fuzzy classifiers and genetic programming- state of the art and prospective approaches
Original language description
There are various techniques for data mining and data analysis. Data mining is very important in the information retrieval areas especially when the data amounts are very large. Among them, hybrid approaches combining two or more algorithms gain importance as the complexity and dimension of real world data sets grows. In this paper, we present an application of evolutionary-fuzzy classification technique for data mining, outline state of the art of related methods and draw future directions of the research. In the presented application, genetic programming was deployed to evolve a fuzzy classifier and an example of real world application was presented.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)