Hello ,
I went through the tutorial 15:Learning Structure .
I took for example the "retention.txt" data set.
Data -> Learn New Network - > pc (All by the example) but i get some new screen by the name : "Pattern Editor-PC" and when i pressed "Only Create Structure" i get the error "Pattern is not DAG...."
What is that screen and why i can not only get the structure from the data like the tutorial present ?
Another Question:
Supposing i got the Learned the Bayesian Network , can i store the result at Text file for using it later in my code?
Thanks in advance ,
Boris
Learning Structure
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Re: Learning Structure
The tutorial was written before we changed our PC implementation. The new implementation creates the structure from data, but the structure is not necessarily a directed acyclic graph (DAG) - it can contain cycles and/or uni- and bi-directional links. This structure must become a DAG before SMILE/GeNIe can use it to create a BN - this is the reason for the new dialog box.borisrabin wrote:Data -> Learn New Network - > pc (All by the example) but i get some new screen by the name : "Pattern Editor-PC" and when i pressed "Only Create Structure" i get the error "Pattern is not DAG...."
What is that screen and why i can not only get the structure from the data like the tutorial present ?
You can store it using any file format which is supported by SMILE. All of them are text-based.Supposing i got the Learned the Bayesian Network , can i store the result at Text file for using it later in my code?
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Re: Learning Structure
* What is the new structure represent?shooltz wrote:The tutorial was written before we changed our PC implementation. The new implementation creates the structure from data, but the structure is not necessarily a directed acyclic graph (DAG) - it can contain cycles and/or uni- and bi-directional links. This structure must become a DAG before SMILE/GeNIe can use it to create a BN - this is the reason for the new dialog box.borisrabin wrote:Data -> Learn New Network - > pc (All by the example) but i get some new screen by the name : "Pattern Editor-PC" and when i pressed "Only Create Structure" i get the error "Pattern is not DAG...."
What is that screen and why i can not only get the structure from the data like the tutorial present ?
You can store it using any file format which is supported by SMILE. All of them are text-based.Supposing i got the Learned the Bayesian Network , can i store the result at Text file for using it later in my code?
* How can i build BN from my data (with this new structure representation ), when my main purpose is finding dependency between
attributes?
I attached DB for example.
Thanks,
Boris
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Re: Learning Structure
Your post contains no attachments.I attached DB for example.
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Re: Learning Structure
shooltz wrote:Your post contains no attachments.I attached DB for example.
- Attachments
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- Database1.zip
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- (85.11 KiB) Downloaded 293 times
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- Database1.rar
- Data Base
- (70.73 KiB) Downloaded 310 times
Re: Learning Structure
The new structure denotes a direct dependency between variables when an edge exists, and edges are oriented if the algorithm could decide it should be. You can build a BN from this structure by creating a DAG out of it.borisrabin wrote:* What is the new structure represent?
* How can i build BN from my data (with this new structure representation ), when my main purpose is finding dependency between
attributes?
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- Joined: Thu Sep 30, 2010 7:48 pm
Re: Learning Structure
Thanks for your answer,mark wrote:The new structure denotes a direct dependency between variables when an edge exists, and edges are oriented if the algorithm could decide it should be. You can build a BN from this structure by creating a DAG out of it.borisrabin wrote:* What is the new structure represent?
* How can i build BN from my data (with this new structure representation ), when my main purpose is finding dependency between
attributes?
My only purpose is to learn Bayesian Network from Database (Attached above) which represent dependency between attributes .
How i can do it directly without getting this intermediate stage ? Which algorithm i should choose ? maybe i need to discrete my variable ?
Thanks in advance ,
Boris
Re: Learning Structure
PC is the only option for continuous data, otherwise you need to discretize.