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HUGIN GUI Discussion / How to classify data
« Last post by Ivana Cace on January 30, 2015, 23:25:43  »
I have a Bayesian Network, and i have loaded a data-file. But i cannot find how to classify the data, that is, how to assign a joint probability to each data-point (row) according to the BN.

I am probably missing something obvious.  ???
In the data-window menu i can choose: model > select a run mode model
But when i select my BN nothing happens.

HUGIN GUI Discussion / Re: Panorama has a white blur
« Last post by Anders L Madsen on January 20, 2015, 11:22:01  »
HUGIN GUI Discussion / Panorama has a white blur
« Last post by Magnus Schmidt on January 16, 2015, 22:11:50  »

 I have some problems with a large panorama (42 images, 180 degrees, several rows, photographed with a DSLR).

Part of the panorama is a direct view of the sun. When rendering the panorama with Hugin, the result gets a white blur, some milky finish. I have uploaded a downsampled version of the result here:

I have tried to get rid of the blur using various settings, but I haven't found anything, that removes the milky finish. All three output methods (simple Interface) are creating this problem. I also adjusted the brightness levels of the input-images in Lightroom, but that doesn't make any difference.

Has anyone any ideas or hints how to get the panorama right?

It isn't clear to me what you're trying to achieve.  Could you give some examples?
As a novice Hugin user and oriented to risk modelling applications, I am interested in using Boolean variables/nodes, however, the point values specified for parents for true and false states seem dull. Is it possible somehow to use "simple" distribution data (e.g, log-normal) for true state(s) and rest to 1 is set to false state?
Had read the Expressions chapter in Manual, and Distrubution () function as permitted for Boolean nodes is not clear enough for me.
General Discussion / Re: Expressions
« Last post by Frank Jensen on December 18, 2014, 15:25:30  »
I don't think there is an elegant way to do this.

However, if we assume that "f(y|z)" can be expressed using Hugin expression syntax, and we know that Z assumes one of a finite number of states, say z1, z2, and z3, then you can write max_z{f(y|z)} as follows:

max (f(y|z1), f(y|z2), f(y|z3))

Clearly not pretty, but it should work.

General Discussion / Re: Expressions
« Last post by Therese on December 17, 2014, 13:02:27  »
Here is an example:

I have a discrete binary node X, and an observation y which has a continuous distribution with density f(y | z) given a discrete network variable Z. I want to define the distribution of X | Z using the distribution of y. We may think of y as a fixed quantity that is used when building the network.

If I simply want

P(X = 1 | Z = z) = P(Y < y | Z = z),

I think that this could perhaps be done by instead making X an interval node with states [-inf, y] and [y, inf].

Now, sometimes I want to let

P(X = 1 | Z = z) = f(y | z)/k

and then P(X = 0 | Z = z) = 1 - P(X = 1 | Z = z).

This is more difficult for two reasons.

The first reason is the essence of my question: I need to be able to evaluate the density f in this arbitrary point y.

The other reason is that I need to identify a constant k so that f(y | z)/k becomes a well defined probability. When I create tables by hand, I may do this simply by taking k to be max_z{f(y | z)}. I suspect that this will not be possible, because the expression is naturally defined for only one state z of Z.

I hope that my question makes sense. Hugin already computes everything I need like a charm. I'm simply exploring other ways of doing the same thing ;)

General Discussion / Re: Expressions
« Last post by Frank Jensen on December 16, 2014, 23:01:06  »
Hi Therese,

You can use Normal, LogNormal, and Gamma in expressions, see section 6.7.1 in the Hugin API Reference Manual.

But I suspect that it is not as simple as that.  Can you elaborate on the "slightly complicated to compute" part of your post?

General Discussion / Expressions
« Last post by Therese on December 16, 2014, 19:10:30  »

I have some rather large probability tables, where the probabilities are slightly complicated to compute in that they involve evaluating the pdf and cdf of a standard (continuous) family of distributions, e.g. the normal, lognormal, and gamma distributions.

Would it be possible for me to specify this by expressions rather than manually specifying the tables?
I suspect that perhaps not judging from the the set of building blocks for expressions that are given in C API and the GUI help pages, but I may have overlooked something.

All the best,
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