Conditional Independence

#artificialintelligence 

When it comes to probability theory we all would have heard of joint distribution, marginal distribution, independence etc. In this article I will focus my attention onto independence specially conditional independence. In others words if the happening of event A doesn't affect the probability of event B happening, both events are said to be independent. From the view of information theory it can be interpreted as: if knowing A doesn't provide any additional information about B, then A and B are said to be independent. These are the different interpretations for the concept of independence.

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