An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical Models

Jens Dalgaard Nielsen, Manfred Jaeger

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Abstrakt

In this paper we compare Na\ii ve Bayes (NB) models, general Bayes Net (BN) models and Probabilistic Decision Graph (PDG) models w.r.t. accuracy and efficiency. As the basis for our analysis we use graphs of size vs. likelihood that show the theoretical capabilities of the models. We also measure accuracy and efficiency empirically by running exact inference algorithms on randomly generated queries. Our analysis supports previous results by showing good accuracy for NB models compared to both BN and PDG models. However, our results also show that the advantage of the low complexity inference provided by NB models is not as significant as assessed in a previous study.
OriginalsprogEngelsk
TitelProceedings of the Third European Workshop on Probabilistic Graphical Models
Antal sider8
Publikationsdato2006
Sider215-222
StatusUdgivet - 2006
BegivenhedEuropean Workshop on Probabilistic Graphical Models - Prag, Tjekkiet
Varighed: 12 sep. 200615 sep. 2006
Konferencens nummer: 3

Konference

KonferenceEuropean Workshop on Probabilistic Graphical Models
Nummer3
LandTjekkiet
ByPrag
Periode12/09/200615/09/2006

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