Answers.Body: <p>A bayesian network where the random variables represented can be continuous or discrete. Usually the continuous variables are handled with Normal distribution with an input of some linear combination of the variables it is dependent on.</p>
  
  <p>Much more detail can be found in Koller's Probabilistic Graphical Model book: <a href="http://pgm.stanford.edu/" rel="nofollow noreferrer">http://pgm.stanford.edu/</a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-12-06T19:09:39.110Z
Answers.LastActivityDate: 2018-12-06T19:09:39.110Z
Answers.UserDisplayName: sma
Body: <p>The field of artificial intelligence is so vast. There are many methodologies for handling continuous data, and I have just read about the <em>hybrid Bayesian network</em>. I just want to know that what a hybrid Bayesian network contains?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-12-06T17:14:58.867Z
Comments.Text: Have a look at http://people.cs.aau.dk/~tdn/papers/langseth-etal-09.pdf
Comments.UserDisplayName: Oliver Mason
Tags: <bayesian-networks><probabilistic-graphical-models><probabilistic-machine-learning>
Title: What does a hybrid Bayesian network contain?
UserDisplayName: saiqa jabeen
ThreadText: # What does a hybrid Bayesian network contain?
  
  (Asked by: username_0 on 2018-12-06)
  
  The field of artificial intelligence is so vast. There are many methodologies for handling continuous data, and I have just read about the *hybrid Bayesian network*. I just want to know that what a hybrid Bayesian network contains?
  
  **Tags:** bayesian-networks, probabilistic-graphical-models, probabilistic-machine-learning
  > **Comments:**
  > **username_1**: Have a look at http://people.cs.aau.dk/~tdn/papers/langseth-etal-09.pdf  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2018-12-06. Score: 0 | Accepted answer
  
  A bayesian network where the random variables represented can be continuous or discrete. Usually the continuous variables are handled with Normal distribution with an input of some linear combination of the variables it is dependent on.
  
  Much more detail can be found in Koller's Probabilistic Graphical Model book: <http://pgm.stanford.edu/>
  
  
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