Stepwise regression clustering method in function points estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63522743" target="_blank" >RIV/70883521:28140/19:63522743 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-00211-4_29" target="_blank" >http://dx.doi.org/10.1007/978-3-030-00211-4_29</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-00211-4_29" target="_blank" >10.1007/978-3-030-00211-4_29</a>
Alternative languages
Result language
angličtina
Original language name
Stepwise regression clustering method in function points estimation
Original language description
This study proposed a stepwise regression clustering method for software development effort estimation. The proposed algorithm is based on functional points analysis and is used for forming clusters, which contains analogical projects. Furthermore, it is expected that clusters will be shaped well for the regression prediction models. The proposed models are based on Cook distance, which is used for elimination project from clusters. Model performance is proved for selected clusters. Overall model performance influenced by selected clusters, therefore, there is no statistically significant difference between regression models based on clustered and un-clustered datasets.
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
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
COMPUTATIONAL AND STATISTICAL METHODS IN INTELLIGENT SYSTEMS
ISBN
978-3-030-00210-7
ISSN
2194-5357
e-ISSN
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Number of pages
8
Pages from-to
333-340
Publisher name
Springer
Place of publication
Cham
Event location
Szczecin
Event date
Sep 12, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000502603900029