Learning parameters in a diagnostic model
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Learning parameters in a diagnostic model
I have developed a model for product development based on a diagnostic structure, e.g., all chance modules with targets, observations and auxiliary nodes. I have base definitions/probabilities entered into the property sheets but want to tighten up the model by learning parameters. I have tried to learn how to do this with a simple model included with tuturials the "AsiaDiagnosis" model. I have created a text data file and loaded this with the model. When I activate learn parameters, everything seems to line up well between nodes and states, however, Genie fails to learn parameters and I get an error message "em: network and dataset do not match". I do not understand why I am getting this message but suspect that it may be due to the difference in what I am doing and the very simple example in the Genie documentation which has only auxiliary nodes. Can anyone help me understand what I am doing wrong? Do target, observatory nodes need to be handled differently?
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Re: Learning parameters in a diagnostic model
The message you're seeing is emitted when:
a) data file contains a mix of discrete and continuous data columns
or
b) network has a mix of discrete and continuous models
or
c) network has deterministic or noisyAdder nodes which are not fixed
a) data file contains a mix of discrete and continuous data columns
or
b) network has a mix of discrete and continuous models
or
c) network has deterministic or noisyAdder nodes which are not fixed
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- Posts: 8
- Joined: Tue Feb 19, 2013 9:43 pm
Re: Learning parameters in a diagnostic model
You were correct with option c. There was one deterministic node. Is it true that I can set this and then solve for the other parameters? Do I need to eliminate the column of data for that node or can the node state still be set by discretized data?
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Re: Learning parameters in a diagnostic model
You'll need to add mark the deterministic node as fixed. Click the "Fixed nodes" button in the lower-left corner of "Match Network and Data" window and proceed accordingly.tstephens3956 wrote:You were correct with option c. There was one deterministic node. Is it true that I can set this and then solve for the other parameters? Do I need to eliminate the column of data for that node or can the node state still be set by discretized data?
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- Posts: 8
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Re: Learning parameters in a diagnostic model
Yes, that worked. I wonder while you are on a role if I can ask another question encountered on my way to this learning example. In trying to import data from an Excel file, I get essentially only an empty table. I have worked the tutorial example importing data from Microsoft Access and that works for me resulting in a table that I can adjust for missing values etc, however, Excel does not. All I get with Excel is an empty table.