Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/13755
Title: | Reliable confidence intervals for software effort estimation |
Authors: | Andreou, Andreas S. Papadopoulos, Harris Papatheocharous, Efi |
Major Field of Science: | Engineering and Technology |
Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering |
Keywords: | Forecasting;Learning systems;Conformal predictor |
Issue Date: | Apr-2009 |
Source: | 5th IFIP Conference on Artificial Intelligence Applications and Innovations, AIAI 2009; Thessaloniki; Greece; 23 April 2009 through 25 April 2009; Code 100720 |
Volume: | 475 |
Conference: | International Conference on Artificial Intelligence Applications and Innovations |
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. |
Description: | CEUR Workshop Proceedings Volume 475, 2009, Pages 211-220 |
ISSN: | 1613-0073 |
Type: | Conference Papers |
Affiliation : | University of Cyprus Frederick University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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