[graph-tool] Model Selection across Distributions

Tiago de Paula Peixoto tiago at skewed.de
Mon Nov 30 13:44:24 CET 2020


Am 30.11.20 um 10:29 schrieb kicasta:
> Hi all,
> 
> I´d have a question regarding model selection with different distributions.
> When we want to decide the partition that best describes the data for a
> given distribution we go with that that gives the smallest entropy. However
> say we want to compare 2 different distributions d1 and d2 and the best fit
> for d1 gives an entropy value of e1 and for d2 e2 respectively. If e1 < e2,
> can we say that d1 describes better our data than d2?

Could you be more specific about to which "distributions" you are 
referring? Are you talking about edge covariates?

If so, model selection is explained here:

https://graph-tool.skewed.de/static/doc/demos/inference/inference.html#id28

In this case, the entropy* itself is not enough, you have to consider 
also the derivative terms, as is explained in the above.

(The term "entropy" is actually misleading in this context, since the 
value refers to a log-density rather than a log-probability.)

Best,
Tiago

-- 
Tiago de Paula Peixoto <tiago at skewed.de>
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