DocumentCode
3060994
Title
Column Pruning Beats Stratification in Effort Estimation
Author
Jalali, Omid ; Menzies, Tim ; Baker, Dan ; Hihn, Jairus
Author_Institution
West Virginia Univ., Morgantown
fYear
2007
fDate
20-26 May 2007
Firstpage
7
Lastpage
7
Abstract
Local calibration combined with stratification, also known as row pruning, is a common technique used by cost estimation professionals to improve model performance. The results presented in this paper raise several serious questions concerning the benefits of row pruning for improving effort estimation indicating the need to rethink standard practice. Firstly, the mean size of improvements from row pruning appears to be relatively small compared to the size of the standard deviations in effort estimation data. Secondly, the advantages of row pruning especially for the purposes of deleting spurious outliers can be achieved using column pruning much more effectively. Hence, we advise against row pruning and advocate column pruning instead.
Keywords
estimation theory; software cost estimation; software development management; column pruning; cost estimation; effort estimation; row pruning; Calibration; Costs; Laboratories; Management training; NASA; Predictive models; Propulsion; Resource management; Training data; US Government;
fLanguage
English
Publisher
ieee
Conference_Titel
Predictor Models in Software Engineering, 2007. PROMISE'07: ICSE Workshops 2007. International Workshop on
Conference_Location
Minneapolis, MN
Print_ISBN
0-7695-2954-2
Type
conf
DOI
10.1109/PROMISE.2007.3
Filename
4273263
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