USING TABLES TO LEARN TREES

Systems and methods are described that facilitate learning a Bayesian network with decision trees via employing a learning algorithm to learn a Bayesian network with complete tables. The learning algorithm can comprise a search algorithm that can reverse edges in the Bayesian network with complete t...

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Bibliographic Details
Main Author CHICKERING DAVID M
Format Patent
LanguageEnglish
Published 16.05.2006
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Systems and methods are described that facilitate learning a Bayesian network with decision trees via employing a learning algorithm to learn a Bayesian network with complete tables. The learning algorithm can comprise a search algorithm that can reverse edges in the Bayesian network with complete tables in order to refine a directed acyclic graph (DAG) associated therewith. The refined complete-table DAG can then be employed to derive a set of constraints for a learning algorithm employed to grow decision trees within the decision-tree Bayesian network.
Bibliography:Application Number: KR20050025019