Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10366620 | Information and Software Technology | 2005 | 13 Pages |
Abstract
In the area of software cost estimation, various methods have been proposed to predict the effort or the productivity of a software project. Although most of the proposed methods produce point estimates, in practice it is more realistic and useful for a method to provide interval predictions. In this paper, we explore the possibility of using such a method, known as ordinal regression to model the probability of correctly classifying a new project to a cost category. The proposed method is applied to three data sets and is validated with respect to its fitting and predictive accuracy.
Related Topics
Physical Sciences and Engineering
Computer Science
Human-Computer Interaction
Authors
Panagiotis Sentas, Lefteris Angelis, Ioannis Stamelos, George Bleris,