'Map hypothesis' diaporamas de présentation

Machine Learning

Machine Learning. Probability and Bayesian Networks. An Introduction. Bayesian Decision Theory came long before Version Spaces, Decision Tree Learning and Neural Networks. It was studied in the field of Statistical Theory and more specifically, in the field of Pattern Recognition.

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Data Mining

Data Mining. Lecture 11. Course Syllabus. Classification Techniques ( Week 7- Week 8- Week 9 ) Inductive Learning Decision Tree Learning Association Rules Neural Networks Regression Probabilistic Reasoning Bayesian Learning

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Bayesian Learning

Bayesian Learning. Slides adapted from Nathalie Japkowicz and David Kauchak. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?. Bayesian Learning. Increasingly popular framework for learning

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Wednesday, 28 February 2007 William H. Hsu Department of Computing and Information Sciences, KSU

Lecture 19 of 42. MAP and MLE continued, Minimum Description Length (MDL). Wednesday, 28 February 2007 William H. Hsu Department of Computing and Information Sciences, KSU http://www.kddresearch.org Readings for next class: Chapter 5, Mitchell. Lecture Outline.

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