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DTSTART:20070311T020000
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DTSTART:20071104T020000
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DTSTAMP:20221201T181640
DTSTART;TZID=America/Detroit:20221201T140000
DTEND;TZID=America/Detroit:20221201T150000
SUMMARY:Workshop / Seminar:Special Events Seminar
DESCRIPTION:This talk will review the classical tree augmented naive Bayes classifier (TAN) and then present two alternative learning approaches. The first approach automatically controls the number of edges supported by the training examples in the Bayesian network classifier by adopting a Bayes factor strategy\, yielding more realistic network structures. In the second approach\, we construct TAN classifiers without estimating conditional mutual information. Instead\, the model learns the weights from the data using an evolution strategy to obtain a good classification performance. Applications of these learning approaches will be presented for Twitter sentiment analysis and Orthodontics. Speaker(s): Gonzalo Ruz (Universidad Adolfo Ibáñez)
UID:101641-21801629@events.umich.edu
URL:https://events.umich.edu/event/101641
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:Weiser Hall - 10th Floor
CONTACT:
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