Re: [graph-tool] Model Selection across Distributions

[Tiago de Paula Peixoto]

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?

If so, model selection is explained here:

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





Best,
Tiago

--
Tiago de Paula Peixoto <ti...@skewed.de>

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

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