Universal Training and Validation Script

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TJetter
Posts: 346
Joined: Sat 13. Oct 2012, 12:04

Universal Training and Validation Script

Post by TJetter »

This is a training and validation script which can be used with most time invariant neural net applications. For time variant nets used for time series prediction take a look here instead: viewtopic.php?f=14&t=327

The script loads a neural net as well as a training and a validation data set (lessons). It trains the net and visualizes the reaction of the net in response to both training and validation data, Finally, the script exports the net's reaction to the validation data into a csv file. The export contains the validation inputs, the validation outputs of the net and the original validation target output data.
The latest version of the script (only compatible with MemBrain V7.3.0.0 and higher) also exports the same data for the training lesson and additionally generates a csv file of the net error graph.

The script contains several adjustable parameters like timings and file names. A comment block in the beginning of the script explains the detailed functionalities.

Simply unzip the file into a separate folder. Then copy your neural net, your training and your validation lessons (mbl files) into the same folder, adjust the file names in the script 'TrainValidate.as' according to the copied files and execute the script file via the MemBrain menu option <Scripting><Execute Script>.
The script exits automatically after the time period which has been configured in the constants section of the script.
<Edit 17 Jan 2017>
Replaced zip files. 3 zip files available now for backwards compatibility with older MemBrain versions.
Attachments
TrainValidate.zip
Universal training and validation script
For MemBrain version 7.3.0.0 and newer
(23.71 KiB) Downloaded 1271 times
TrainValidate_UpTo_07_02_xx_xx.zip
For older MemBrain versions up to 7.2.x.x
(24.38 KiB) Downloaded 1255 times
TrainValidate_V5.zip
For older MemBrain versions up to 5.x.x.x
(3.45 KiB) Downloaded 1391 times
Thomas Jetter
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