Improving Algorithmic Optimisation Method by Spectral Clustering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517639" target="_blank" >RIV/70883521:28140/17:63517639 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-57141-6_1" target="_blank" >http://dx.doi.org/10.1007/978-3-319-57141-6_1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-57141-6_1" target="_blank" >10.1007/978-3-319-57141-6_1</a>
Alternative languages
Result language
angličtina
Original language name
Improving Algorithmic Optimisation Method by Spectral Clustering
Original language description
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).
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
SOFTWARE ENGINEERING TRENDS AND TECHNIQUES IN INTELLIGENT SYSTEMS, CSOC2017, VOL 3 Book Series: Advances in Intelligent Systems and Computing
ISBN
978-3-319-57141-6
ISSN
2194-5357
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
"nestrankovano"
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Zlín
Event date
Apr 26, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000405338500001