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Hi all this is artificial intelligence class from udacity. I have a question. P(R0)=1 means probability of day0 rainy is is 1. Here is my question P(R2 | H1 G2)? meaning we know I am happy at day1 and grumpy at day2 what is probability it is raining at day2

Sergei Lebedev
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trial
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    Could you explain what difficulties you're facing answering this yourself? Also, it would help if you give some context for those unfamiliar with the Udacity course. – Sergei Lebedev Jan 02 '17 at 00:15

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Some useful data

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P(R_2|H_1, G_2) can be reduced to P(R_2|G_2) because there is no given transition coeffs. between moods (this can be discovered for a weather sequence however). 

P(R_2|G_2) = P(G_2|R_2)*P(R_2)/P(G_2) = 0.264*0.440/0.320 = 0.363
marmeladze
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  • I could not understand how did you reduced P(R_2|H_1, G_2) into P(R_2|G_2). Can you explain please – trial Jan 05 '17 at 20:47
  • The link https://www.ifi.uzh.ch/dam/jcr:00000000-2826-155d-ffff-ffff86200612/f-chapter4.pdf figure 4.3 how can p(R2|S1,W2) calculated? (It means what is the probability of rain at day 2 if I walked day2 and shoped at day1 )I dont want answer. Just want to learn how to write this bayeasian formula with 3 paramaters. – trial Jan 05 '17 at 22:05