What is a latent variable?

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Latent nodes introduce the problem of missing data. This results in more complicated likelihood calculations, for which we have to find a remedy in another video

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Timestamps:
0:00 Opening
0:18 Observable Nodes
2:27 Latent Nodes
4:00 Problem with latent nodes
5:24 Solution by Marginalization?
  1. Machine Learning & Simulation
  2. latent parameter
  3. hidden variable
  4. directed graphical models
  5. bayes nets
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Комментарии
Автор

This is really an excellent video! The best examples I've seen on latent variables!

indiajackson
Автор

New to this and I have a question... Why do we have to calculate the joint P(T, w) in the first place.

Is it because we need to infer something about 'w', but 'w' itself depends on 'T'. In that case we will have a conditional probability to solve in order to infer i.e. P(w/T)...
We know, P(w/T)=P(w, T)/P(T)....So here we have the joint P(w, T) which we need to this reasoning correct to understand why we need to solve the joint distribution P(w, T) in the first place?


Somewhere i saw that it was the other way round i.e. we need to calculate P(T/w).... but that does not intuitively fit in because in the diagram you made the arrow is from 'w' to 'T'... so "T' depends on

Omar-rcli
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i can't believe that you have just spelled "happyness" with "Y"...

UpperM