LFD Book Forum Clarification of Conditional Probability Interpretation
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#1
01-05-2017, 05:34 PM
 tushar Junior Member Join Date: Jan 2017 Posts: 2
Clarification of Conditional Probability Interpretation

Let's say x is determined by a normal distribution and p(y|x) is a sigmoid function if y = 1 and the sigmoid reflected along the vertical axis if y = -1.

p(y|x) = {
f(x) if y = 1
1 - f(x) if y = -1
}

Then p(x, y) = p(y|x) * p(x)

So for the case y = 1, does it make sense to say that p(x, y) is just the multiple of the sigmoid function and the normal distribution?﻿
#2
01-06-2017, 02:57 AM
 tushar Junior Member Join Date: Jan 2017 Posts: 2
Re: Clarification of Conditional Probability Interpretation

Never mind: the joint probability distribution actually integrates to 1 so the formulation is correct. How can I delete the thread?

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