Scope classification: An instance-based learning algorithm with a rule-based characterisation
Identifieur interne : 00B324 ( Main/Exploration ); précédent : 00B323; suivant : 00B325Scope classification: An instance-based learning algorithm with a rule-based characterisation
Auteurs : Nicolas Lachiche [France] ; Pierre Marquise [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: Scope classification is a new instance-based learning (IBL) technique with a rule-based characterisation. Within the scope approach, the classification of an object o is based on the examples that are closer to o than every example labelled with another class. In contrast to standard distance-based IBL classifiers, scope classification relies on partial preorderings ≤o between examples, indexed by objects. Interestingly, the notion of closeness to o that is used characterises the classes predicted by all the rules that cover o and are relevant and consistent for the training set. Accordingly, scope classification is an IBL technique with a rule-based characterisation. Since rules do not have to be explicitly generated, the scope approach applies to classification problems where the number of rules prevents them from being exhaustively computed.
Url:
DOI: 10.1007/BFb0026697
Affiliations:
- France
- Grand Est, Hauts-de-France, Lorraine (région), Nord-Pas-de-Calais
- Lens (Pas-de-Calais), Vandœuvre-lès-Nancy
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Within the scope approach, the classification of an object o is based on the examples that are closer to o than every example labelled with another class. In contrast to standard distance-based IBL classifiers, scope classification relies on partial preorderings ≤o between examples, indexed by objects. Interestingly, the notion of closeness to o that is used characterises the classes predicted by all the rules that cover o and are relevant and consistent for the training set. Accordingly, scope classification is an IBL technique with a rule-based characterisation. Since rules do not have to be explicitly generated, the scope approach applies to classification problems where the number of rules prevents them from being exhaustively computed.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Hauts-de-France</li><li>Lorraine (région)</li><li>Nord-Pas-de-Calais</li></region><settlement><li>Lens (Pas-de-Calais)</li><li>Vandœuvre-lès-Nancy</li></settlement></list><tree><country name="France"><region name="Grand Est"><name sortKey="Lachiche, Nicolas" sort="Lachiche, Nicolas" uniqKey="Lachiche N" first="Nicolas" last="Lachiche">Nicolas Lachiche</name></region><name sortKey="Lachiche, Nicolas" sort="Lachiche, Nicolas" uniqKey="Lachiche N" first="Nicolas" last="Lachiche">Nicolas Lachiche</name><name sortKey="Marquise, Pierre" sort="Marquise, Pierre" uniqKey="Marquise P" first="Pierre" last="Marquise">Pierre Marquise</name><name sortKey="Marquise, Pierre" sort="Marquise, Pierre" uniqKey="Marquise P" first="Pierre" last="Marquise">Pierre Marquise</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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