APPrOVE: Application-oriented Validation and Evaluation of Supervised Learners
| Document type: | Conference Papers |
|---|---|
| Peer reviewed: | Yes |
| Full text: | |
| Author(s): | Niklas Lavesson, Paul Davidsson |
| Title: | APPrOVE: Application-oriented Validation and Evaluation of Supervised Learners |
| Conference name: | IEEE Intelligent Systems |
| Year: | 2010 |
| Pagination: | 150-155 |
| ISBN: | 978-1-4244-5164-7 |
| Publisher: | IEEE press |
| City: | London |
| Organization: | Blekinge Institute of Technology |
| Department: | School of Computing (Sektionen för datavetenskap och kommunikation) School of Computing S-371 79 Karlskrona +46 455 38 50 00 http://www.bth.se/com |
| Authors e-mail: | niklas.lavesson@bth.se, paul.davidsson@bth.se |
| Language: | English |
| Abstract: | Learning algorithm evaluation is usually focused on classification performance. However, the characteristics and requirements of real-world applications vary greatly. Thus, for a particular application, some evaluation criteria are more important than others. In fact, multiple criteria need to be considered to capture application-specific trade-offs. Many multi-criteria methods can be used for the actual evaluation but the problems of selecting appropriate criteria and metrics as well as capturing the trade-offs still persist. This paper presents a framework for application-oriented validation and evaluation (APPrOVE). The framework includes four sequential steps that together address the aforementioned problems and its use in practice is demonstrated through a case study. |
| Subject: | Computer Science\Artificial Intelligence Software Engineering\General |
| Keywords: | classification, evaluation, supervised learning |
