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Neural Clustering Agent Properties and Use

Properties

The Neural Clustering Agent panel provides these options:

Training File Name
Enter the name of a definition file. Use the Browse button to select a definition file. This file will be used to specify the network architecture's input value since it defines the number of fields and their data type. The data itself must be a file by the same name with a .dat extension. This will be used when the mode is Train and also to Generate Beans.
Testing File Name
Enter the name of a definition file with the same layout as the training definition file. Use the Browse button to select a definition file. This will be used when you set the mode to Test.
Agent Mode
Select one of the following agent modes:
Train implies that the network bean's weights are unlocked, and the import bean referencing the Training File provides the active data buffer connection.
Test implies that the network bean's weights are locked, and the percent correct is calculated; the import bean referencing the Testing File provides the active data buffer connection.
Run implies that the network bean's weights are locked and the percent correct is not calculated.
Network Architecture
The architecture consists of these parameters:
  1. Inputs, which is calculated when beans are generated from the Training File.
  2. Output rows, which is the number of rows in the network bean's output layer.
  3. Output columns, which is the number of columns in the network bean's output layer.
Maximum Number of Passes
The threshold value for the maximum number of passes. Training the network will stop if this threshold is attained.

Use

The Neural Clustering Agent panel is used to generate an agent containing import beans for training and testing, a SelfOrganizingMap bean, filter beans to translate network inputs and outputs, and data connections. The Agent Mode is set so that the network bean can be trained or used to provide an independant data source to test that training is sufficient.

Steps in using the panel for training include:

  1. Enter the name of the training file that defines the record layout and name of the training data source. If the file is read successfully, the Generate Beans button should be enabled.
  2. Select Train for the Agent Mode.
  3. Set the values for dimensions of the output.
  4. Press the Generate Beans button. The Start Training button should now be enabled.
  5. Set the Maximum Passes threshold to control when training will stop.
  6. Press the Start Training button to begin processing records through the data buffer connections. Once training has begun, this button will toggle to Stop Training. Training will continue until the toggled button is pressed, or the Maximum Passes value is attained.
  7. You may wish to press the Stop Training button, change the threshold, and start again. If you change the network architecture, press Generate Beans for the changes to take effect. Press the Reset Beans button to re-initialize the network weights before starting training again if you wish.

For a description of the agent output, see the SelfOrganizingMap bean use.