Very Fast Decision Rules for Multi-class Problems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F12%3A00059330" target="_blank" >RIV/00216224:14330/12:00059330 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Very Fast Decision Rules for Multi-class Problems
Original language description
Decision rules are one of the most interpretable and flexible models for data mining prediction tasks. Till now, few works presented on-line, any-time and one-pass algorithms for learning decision rules in the stream mining scenario. A quite recent algorithm, the Very Fast Decision Rules (VFDR), learns set of rules, where each rule discriminates one class from all the other. In this work we extend the VFDR algorithm by decomposing a multi-class problem into a set of two-class problems and inducing a setof discriminative rules for each binary problem. The proposed algorithm maintains all properties required when learning from stationary data streams: on-line and any-time classifiers, processing each example once. Moreover, it is able to learn ordered and unordered rule sets. The new approach is evaluated on various real and artificial datasets. The new algorithm improves the performance of the previous version and is competitive with the state-of-the-art decision tree learning method f
Czech name
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Czech description
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Project
<a href="/en/project/LA09016" target="_blank" >LA09016: Czech Republic membership in the European Research Consortium for Informatics and Mathematics (ERCIM)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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