Document Type
Conference Paper
Rights
This item is available under a Creative Commons License for non-commercial use only
Disciplines
Computer Sciences
Abstract
Case-based approaches to classification, as instance-based learning techniques, have a particular reliance on training examples that other supervised learning techniques do not have. In this paper we present the RDCL case profiling technique that categorises each case in a case-base based on its classification by the case-base, the benefit it has and/or the damage it causes by its inclusion in the case-base. We show how these case profiles can identify the cases that should be removed from a case-base in order to improve generalisation accuracy and we show what aspects of existing noise reduction algorithms contribute to good performance and what do not.
Recommended Citation
Delany, S. (2009) The Good, the Bad and the Incorrectly Classified: Profiling Cases for Case-Base Editing. L.McGinty & D. Wilson (eds) International Conference on Case Based Reasoning (ICCBR 2009), LNCS 5650 p.135-149 Springer Verlag. doi:10.1007/978-3-642-02998-1_11
DOI
10.1007/978-3-642-02998-1_11
Publication Details
In: L.McGinty & D. Wilson (eds) International Conference on Case Based Reasoning (ICCBR 2009), LNCS 5650 p.135-149 Springer Verlag