Critiques

Hi Yaashaar, Thanks for the write up. It is indeed a pleasant read, given the way you have taken the bottom up approach. By motivating from an interesting real world example and then connecting that to the theory, which I found very engaging. However I have few suggestions that may further help in bettering it:

• Can you add a section on large scale Bayesian inference. I guess this is a very valid topic given current influence of big data.
• Adding some more references in bibliography, would be helpful to facilitate further reading. For e.g. you may give a little introduction to large scale bayesian and add pointers for detailed reading on that.
• A better formatting would help. For e.g. lines like the following should be formatted better:

In our example we would have required to specify $2^{1}2$ numbers for presenting the full joint probability distributions in the worst case scenario (fully connected network),however, by exploiting the conditional independences among variables through the Bayesian Network, we only defined:

$N\times D^{K}$

• Some of the sentences are very long and hard to follow. Better if the can be split to smaller ones. For e.g:

The idea behind the Bayesian Network and its power is where, by exploiting the conditional independency of a variable giving a subset of its predecessor nodes upon which the random variable directly depends, we can query as if we have the access over the full Joint Probability Distributions (JPD), while in fact, only conditional probability distributions were defined.

• A few quibbles apart from those that already been highlighted.

Bayesian Networks (also referred to as Belief Networks or Probabilistic Networks) is a --> should be are These case are from Death --> These cases

that directly affects variable --> affect

best, Prithu Banerjee

Hi Prithu,

Thank you very much for your careful inspection. I have addressed almost all of the issues you pointed out and I incorporated most of your kind suggestions. Just regarding the Bayesian inference in large scale, I believe that it should be classified under model Inferences, which were discussed in the Graphical Models page. In my opinion, a dedicated page for model inferences is required. With respect to the current size of the page, I would consider any discussion over the Bayesian Inference more than what has been out of the scope.

I really appreciate your comments.
Yaashaar