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Improving algorithmic optimisation method by spectral clustering

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dc.title Improving algorithmic optimisation method by spectral clustering en
dc.contributor.author Šilhavý, Radek
dc.contributor.author Šilhavý, Petr
dc.contributor.author Prokopová, Zdenka
dc.relation.ispartof Advances in Intelligent Systems and Computing
dc.identifier.issn 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9783319571409
dc.date.issued 2017
utb.relation.volume 575
dc.citation.spage 1
dc.citation.epage 10
dc.event.title 6th Computer Science On-line Conference, CSOC 2017
dc.event.sdate 2017-04-26
dc.event.edate 2017-04-29
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Verlag
dc.identifier.doi 10.1007/978-3-319-57141-6_1
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-57141-6_1
dc.subject Algorithmic optimisation method en
dc.subject Clustering en
dc.subject Effort estimation en
dc.subject Use case points en
dc.description.abstract In this paper, a spectral algorithm for effort estimation is evaluated. As effort prediction method the Algorithmic Optimisation Method is employed. Spectral clustering is used in version of normalized Laplacian matrix and k-means algorithm is used for clustering eigenvectors. Results shows that clustering lowers a Mean Absolute Percentage Error by 6% and Sum of Squared Errors/Residuals is decreased by 43,5%. Difference in mean value of residuals is statically significant (p = 0.0041, at 0.05 level). © Springer International Publishing AG 2017. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007386
utb.identifier.obdid 43877552
utb.identifier.scopus 2-s2.0-85018696654
utb.identifier.wok 000405338500001
utb.source d-scopus
dc.date.accessioned 2017-09-08T12:14:49Z
dc.date.available 2017-09-08T12:14:49Z
utb.contributor.internalauthor Šilhavý, Radek
utb.contributor.internalauthor Šilhavý, Petr
utb.contributor.internalauthor Prokopová, Zdenka
utb.fulltext.affiliation Radek Silhavy, Petr Silhavy, Zdenka Prokopova Faculty of Applied Informatics, Tomas Bata University in Zlin, nam T.G. Masaryka 5555, Zlin, Czech Republic {rsilhavy,psilhavy,prokopova}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
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