Cost-sensitive Attribute Value Acquisition for Support Vector
| dc.contributor.author | TAN, Yee Fan | en_US |
| dc.contributor.author | KAN, Min-Yen | en_US |
| dc.date.accessioned | 2010-03-30T06:40:59Z | en_US |
| dc.date.accessioned | 2017-01-23T07:00:14Z | |
| dc.date.available | 2010-03-30T06:40:59Z | en_US |
| dc.date.available | 2017-01-23T07:00:14Z | |
| dc.date.issued | 2010-03-30T06:40:59Z | en_US |
| dc.description.abstract | We consider cost-sensitive attribute value acquisition in classification problems, where missing attribute values in test instances can be acquired at some cost. We examine this problem in the context of the support vector machine, employing a generic, iterative framework that aims to minimize both acquisition and misclassification costs. Under this framework, we propose an attribute value acquisition algorithm that is driven by the expected cost savings of acquisitions, and for this we propose a method for estimating the misclassification costs of a test instance before and after acquiring one or more missing attribute values. In contrast to previous solutions, we show that our proposed solutions generalize to support vector machines that use arbitrary kernels. We conclude with a set of experiments that show the effectiveness of our proposed algorithm. | en_US |
| dc.format.extent | 408123 bytes | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.uri | https://dl.comp.nus.edu.sg/xmlui/handle/1900.100/3110 | en_US |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | TRB3/10 | en_US |
| dc.title | Cost-sensitive Attribute Value Acquisition for Support Vector | en_US |
| dc.type | Technical Report | en_US |