Scope classification : An instance-based learning algorithm with a rule-based characterisation
Identifieur interne : 00B427 ( Main/Exploration ); précédent : 00B426; suivant : 00B428Scope classification : An instance-based learning algorithm with a rule-based characterisation
Auteurs : N. Lachichel [France] ; P. Marquis [France]Source :
- Lecture notes in computer science [ 0302-9743 ] ; 1998.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Intelligence artificielle, Classification.
English descriptors
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 pre-orderings ≤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.
Affiliations:
- France
- Grand Est, Hauts-de-France, Lorraine (région), Nord-Pas-de-Calais
- Lens (Pas-de-Calais), Vandoeuvre-lès-Nancy
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Le document en format XML
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Lachichel</name><affiliation wicri:level="3"><inist:fA14 i1="01"><s1>LORIA, B.P. 239</s1><s2>54506 Vandoeuvre-lès-Nancy </s2><s3>FRA</s3><sZ>1 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region><settlement type="city">Vandoeuvre-lès-Nancy </settlement></placeName></affiliation></author><author><name sortKey="Marquis, P" sort="Marquis, P" uniqKey="Marquis P" first="P." last="Marquis">P. Marquis</name><affiliation wicri:level="3"><inist:fA14 i1="02"><s1>CRIL/Université d'Artois, Rue de l'Université, S.P. 16</s1><s2>62307 Lens</s2><s3>FRA</s3><sZ>2 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Hauts-de-France</region><region type="old region" nuts="2">Nord-Pas-de-Calais</region><settlement type="city">Lens (Pas-de-Calais)</settlement></placeName></affiliation></author></analytic><series><title level="j" type="main">Lecture notes in computer science</title><idno type="ISSN">0302-9743</idno><imprint><date when="1998">1998</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Lecture notes in computer science</title><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithm complexity</term><term>Artificial intelligence</term><term>Classification</term><term>Learning algorithm</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Intelligence artificielle</term><term>Algorithme apprentissage</term><term>Complexité algorithme</term><term>Classification</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Intelligence artificielle</term><term>Classification</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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 pre-orderings ≤<sub>o</sub> 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>Vandoeuvre-lès-Nancy </li></settlement></list><tree><country name="France"><region name="Grand Est"><name sortKey="Lachichel, N" sort="Lachichel, N" uniqKey="Lachichel N" first="N." last="Lachichel">N. Lachichel</name></region><name sortKey="Marquis, P" sort="Marquis, P" uniqKey="Marquis P" first="P." last="Marquis">P. Marquis</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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