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SMD127 Learning with Baysian Network 5.0 poäng | |
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ÄMNE (enl SCB) Datateknik NIVÅ/DJUP B G PROGRAM/TIDSPERIOD / Lp 3, vt03 SPRÅK: Engelska EXAMINATOR Ramin Yasdi Univ lekt FASTSTÄLLD Kursplanen är fastställd av Institutionen för systemteknik 2001-09-24, att gälla från HT2001. FÖRKUNSKAPSKRAV B-level, knowledge in Machine Learning is useful. SYFTE/MÅL To present foundations of methods and algorithms in the area of Bayesian Learning INNEHÅLL A Bayesian network is a graphical model that encodes relationships among variables of interest. When used in conjunction with statistical techniques, the graphical model has several advantages for data analysis. One, because the model encodes dependencies among all variables, it readily handles situations where some data entries are missing. Two, a Bayesian network can be used to learn causal relationships, and hence can be used to gain understanding about a problem domain and to predict the consequences of intervention. Three, because the model has both a causal and probabilistic semantics, it is an ideal representation for combining prior knowledge (which often comes in causal form) and data. Four, Bayesian statistical method in conjunction with Bayesian networks offer an efficient and principled approach for avoiding the over fitting of data. UNDERVISNING Lecture and project. EXAMINATION On project work. KURSENS BETYGSKALA: 3 4 5 MOMENT/PROV | |
| Projekt | 5.0poäng |
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LITTERATUR An Introduction to Bayesian Networks, Finn V.Jensen, UCL Press, 96
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Kontaktperson: Ramin Yasdi Ytterligare kursinformation: http://www.sm.luth.se/~yasdi |
| Universitetet | Student | Forskning | Sök | Kontakta oss | In English |
 LULEÅ TEKNISKA UNIVERSITET Universitetsområdet, Porsön, 971 87 Luleå. Tel. 0920-91 000, fax 0920-91 399 |