Techniques where independent variables (predictors) are used to build binary trees where each leaf node either represents a category to which an estimate belongs to, or a value for an estimate. In order to obtain an estimate one has to traverse tree nodes from root to leaf by selecting the nodes that represent the category or value for the independent variables associated with the case to be estimated.
Published in Chapter:
Web Development Effort Estimation: An Empirical Analysis
Emilia Mendes (The University of Auckland, New Zealand) and Silvia Abrahão (Valencia University of Technology, Spain)
Copyright: © 2008
|Pages: 31
DOI: 10.4018/978-1-59904-847-5.ch002
Abstract
Effort models and effort estimates help project managers allocate resources, control costs and schedule, and improve current practices, leading to projects that are finished on time and within budget. In the context of Web development and maintenance, these issues are also crucial, and very challenging, given that Web projects have short schedules and a highly fluidic scope. Therefore, the objective of this chapter is to introduce the concepts related to Web effort estimation and effort estimation techniques. In addition, this chapter also details and compares, by means of a case study, three effort estimation techniques, chosen for this chapter because they have been to date the ones mostly used for Web effort estimation: Multivariate regression, Case-based reasoning, and Classification and Regression Trees. The case study uses data on industrial Web projects from Spanish Web companies.