[Notice] The last lecture of the course will be on the next Monday, 24 June. After the last talk you have to take examination - Topic is calculation of one hypothesis given some evidences given one simple Baysian Network. =============================================== study pp. 21-22 in neuro.bstu.by/ai/bayes-decision-theory-2012.pdf =============================================== - Kochurka & Davidyuk are given an advantate of skip exam due to their all attendances. - Exam for Sagyan will be on 19 June at 16:00 and no need to attend on 24 June. ========================================================================================================== | Lecture (x12) | Practice | Apr May Jun | May June | 22 29 06 13 13 20 20 27 03 03 10 17 17 19 24 24 | 06 13 20 20 27 03 17 result ----------------------|----------------------------------------------------------------------------------- Kochurka Viachaslau | xx ok ok ok ok ok ok xx ok ok xx ok ok . . . | ok ok ok ok -- -- -- => OK Davidyuk Yuliya | xx ok ok ok ok ok ok xx ok ok xx ok ok . . . | ok ok ok ok ok -- -- => OK Gnenochuk Nataliya | xx ok -- ok ok ok ok xx ok ok xx -- -- exam . . | ok ok ok ok -- -- -- => OK Mariynuk Dzmitry | xx ok -- ok ok -- -- xx -- -- xx -- -- . -- -- | ok ok -- -- -- -- -- Lizun Larysa | xx ok -- -- -- ok ok xx -- -- xx -- -- . -- -- | -- -- -- -- -- -- -- Sagyan Alexey | xx -- ok ok ok ok ok xx -- -- xx ok ok exam . . | ok ok ok ok -- -- -- => OK Nikonovich Valentin | xx -- -- -- -- ok ok xx -- -- xx -- -- . (ok)-- | -- -- -- -- -- -- -- =================================================================================================== 1st 04/29 Bayesian conditional probability p(hypothesis|evidence) & its 5 examples 2nd 05/06 Bayesian Classification with one feature: 1-D Gaussian distribution 3rd 05/13 Bayesian Classification with multiple features: 2-D Gaussian distribution 4th 05/13 What is Bayesian Network? 5th 05/20 Border equation between two classes with 2-D or higher Gaussian distribution 6th 05/20 Examples of Baesian Network 7th 06/03 An algorithm for Inference from Baeysian Network 8th 06/03 Decision making Bayesian network: chance-, desition-, utility-node 9th 06/17 An algorithm to create decision making table 10th 06/17 Dynamic Bayesian network, Hidden Markov Model 11th 06/24 Hidden Markov Model 12th 06/24 Application of Hidden Markov Model to stock market prediction, Summary ---------------------------------------------------------------------------------------------- ... deadline is Saturday of the week at 23:59 1st 05/06 Plot 100 points following N(5,2) 1 0 2nd 05/13 Plot 100 points 2-D Gaussian whose mu = (5,5) and Sigma = 0 1 etc. 3rd 05/20 Obtain border equation between two classes with 2-D Gaussian distribution 4th 05/20 An example of border equation in the case of 3-D Gaussian distribution 5th 05/27 Create your own example of Bayesian network with more than 3 variables 6th 06/03 Create a couple of scinario (some evidences + one hypothesis) under your network or "fish-example," then calculate probability of the hypothesis 7th 06/17 calculate probability of 1-1-1-1-1 of fair dice and unfair dice example ---------------------------------------------------------------------------------------------