InstanceRank: Bringing order to datasets
In this paper we present InstanceRank, a ranking algorithm that reflects the relevance of the instances within a dataset. InstanceRank applies a similar solution to that used by PageRank, the web pages ranking algorithm in the Google search engine. We also present ISR, an instance selection techniqu...
| Authors: | ; ; |
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| Format: | Article |
| Status: | Submitted version |
| Publication date: | 2010 |
| Country: | España |
| Institution: | Universidad de Sevilla (US) |
| Repository: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/100070 |
| Online Access: | https://hdl.handle.net/11441/100070 https://doi.org/10.1016/j.patrec.2009.09.022 |
| Access Level: | Open access |
| Keyword: | Instance-based learning Instance reduction Nearest neighbor PageRank Classification |
| Summary: | In this paper we present InstanceRank, a ranking algorithm that reflects the relevance of the instances within a dataset. InstanceRank applies a similar solution to that used by PageRank, the web pages ranking algorithm in the Google search engine. We also present ISR, an instance selection technique that uses InstanceRank. This algorithm chooses the most representative instances from a learning database. Experiments show that ISR algorithm, with InstanceRank as ranking criteria, obtains similar results in accuracy to other instance reduction techniques, noticeably reducing the size of the instance set. |
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