Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/13755
Title: Reliable confidence intervals for software effort estimation
Authors: Andreou, Andreas S. 
Papadopoulos, Harris 
Papatheocharous, Efi 
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: 1-Dec-2009
Source: CEUR Workshop Proceedings
Abstract: This paper deals with the problem of software effort estimation through the use of a new machine learning technique for producing reliable confidence measures in predictions. More specifically, we propose the use of Conformal Predictors (CPs), a novel type of prediction algorithms, as a means for providing effort estimations for software projects in the form of predictive intervals according to a specified confidence level. Our approach is based on the well-known Ridge Regression technique, but instead of the simple effort estimates produced by the original method, it produces predictive intervals that satisfy a given confidence level. The results obtained using the proposed algorithm on the COCOMO, Desharnais and ISBSG datasets suggest a quite successful performance obtaining reliable predictive intervals which are narrow enough to be useful in practice.
URI: http://ktisis.cut.ac.cy/handle/10488/13755
ISSN: 16130073
2-s2.0-84887253684
https://api.elsevier.com/content/abstract/scopus_id/84887253684
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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