Anthony, Martin 
ORCID: 0000-0002-7796-6044 and Ratsaby, Joel
(2013)
Large margin case-based reasoning.
RUTCOR Research Reports (RRR 2-2013).
Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.
Abstract
The central problem in case based reasoning (CBR) is to infer a solution for a new problem-instance by using a collection of existing problem-solution cases. The basic heuristic guiding CBR is the hypothesis that similar problems have similar solutions. CBR has been often criticized for lacking a sound theoretical basis, and there has only recently been some attempts at formalizing CBR in a theoretical framework, including work by Hullermeier who made the link between CBR and the probably approximately correct (PAC) theoretical model of learning in his `case-based inference' (CBI) formulation. In this paper we present a new framework of CBI which models it as a multi-category classification problem. We use a recently-developed notion of geometric margin of classification to obtain generalization error bounds.
| Item Type: | Monograph (Report) |
|---|---|
| Official URL: | http://rutcor.rutgers.edu/index.html |
| Additional Information: | © 2013 Rutgers, The State University of New Jersey |
| Divisions: | Mathematics |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Date Deposited: | 04 Mar 2013 16:24 |
| Last Modified: | 11 Sep 2025 03:08 |
| Funders: | ST Programme of the European Community, under the PASCAL2 Network of Excellence, IST-2007-216886 |
| URI: | http://eprints.lse.ac.uk/id/eprint/48771 |
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