[R] learning networks with a large number of variables and pre-set parents.

[Christian Schulz]

Hi,

you have 10000 variables and how many cases?
In my experience you need a lot of memory working with this kind/size of
data and deal!

>> dim(pk.df)
[1] 7321 24
>> pk <- network(pk.df)
>> pk.prior <- jointprior(pk)
Error in rep.default(data, length.out = vl) :
cannot allocate vector of length 577368000

Perhaps this is usefuel for you?

Ines - Induction of Network Structure
(learning probabilistic and possibilistic graphical models)

http://fuzzy.cs.uni-magdeburg.de/~borgelt/ines.html

regards,
Christian


zhihua li schrieb:

> hi netters:
> I have a series of discrete variables which form a network and I want
> to learn the network structure from some training data. I could have
> used packages like deal but there are two problems.
> First of all, I have 10000 variables. So the possible network
> structure is awfully huge, I don't know how long it will take my PC to
> find the highest-scoring network..........maybe a month? Secondly, I
> have some prior knowledge that only 500 out of the 10000 variales are
> possible parents. In another word, only those arrows startting from
> the 500 variables and pointing to the remaining 99500 variables are
> allowed in the network. In deal an assignment to "banlist" should help
> me rule out the impossible arrows. But in my case the number of
> "impossible arrows" is 500*499+99500*99549, and so the "banlist" would
> get unacceptable long. Are there any methods (in deal or other
> packages) to specify the parents set in advance?
> Thanks a lot!
>
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