Active Relational Rule Learning in a Constrained Confidence-rated Boosting Framework PDF ePub eBook

Books Info:

Active Relational Rule Learning in a Constrained Confidence-rated Boosting Framework free pdf Boosting is a particularly robust and powerful technique to enhance the prediction accuracy of systems that learn from examples. Although boosting has been extensively studied in the last years for propositional learning systems, only little attention has been paid to boosting in relational learning. The author proposes a successful boosted ILP based relational learning system and an embedded active feature selection technique which together result in learning time reduction of up to three orders of magnitude compared to state-of-the-art ILP learning systems, while maintaining or even enhancing the interpretability an the predictive accuracy of the induced hypotheses. Unlike existing feature selection methods in relational learning, the feature selection technique used here actively determines feature subsets for learning on the basis of the actual learning process, and avoids the transformation of the given examples into a propositional representation. Boosting ist eine besonders robuste und leistungsfahige Methode zur Verbesserung der Vorhersagegenauigkeit von Verfahren, die aus Beispielen lernen. Wahrend der Einsatz von Boosting-Methoden fur propositionale Lernverfahren in den letzten Jahren intensiv untersucht worden ist, spielt diese Technik auf dem Gebiet der relationalen Lernverfahren bisher nur eine untergeordnete Rolle. Die Autorin formuliert ein leistungsfahiges und effizientes geboostetes ILP-basiertes relationales Regellernverfahren und eine Methode zur integrierten aktiven Merkmalsauswahl, die zusammen eine Reduktion der Lernzeitkomplexitat gegenuber etablierten ILP-Lernverfahren um bis zu drei Grossenordnungen erreichen ohne die Vorhersagegenauigkeit oder die Verstandlichkeit der Lernergebnisse zu beeintrachtigen. Das hier angewendete Verfahren bestimmt im Gegensatz zu existierenden Verfahren zur relationalen Merkmalsauswahl aktiv relevante Merkmale auf der Basis des aktuellen Lernprozesses und vermeidet daruber hinaus eine Transformation der gegebene

About Susanne Hoche

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Details Book

Author : Susanne Hoche
Publisher : Kubitza, Heinz-Werner, Dr., Tectum Verlag
Data Published : 30 May 2005
ISBN : 3828888364
EAN : 9783828888364
Format Book : PDF, Epub, DOCx, TXT
Number of Pages : 252 pages
Age + : 15 years
Language : English
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