Hybrid algorithm for learning structure of Bayesian network from incomplete databases

Hybrid algorithm for learning structure of Bayesian network from incomplete databases

Scoring-based and constraint-based algorithms are two approaches for learning BN structure from data. Hybrid algorithm combines these two approaches in order being more efficient. Experimental result shows its superior. The algorithm, then, is modified to overcome incomplete databases. It is expecte...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Saptawati, G.A.P., Sitohang, B.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Asia
Bayesian methods
Data analysis
Data mining
Informatics
Probability distribution
Random variables
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Beschreibung
Zusammenfassung:Scoring-based and constraint-based algorithms are two approaches for learning BN structure from data. Hybrid algorithm combines these two approaches in order being more efficient. Experimental result shows its superior. The algorithm, then, is modified to overcome incomplete databases. It is expected that the proposed algorithm can also show its superiority.
DOI:10.1109/ISCIT.2005.1566960