GUI
NeuralBuilder
Step 1: Model Selection
Step 2: Training Data
Step 3: Cross Validation
Step 4: Topology Config.
Step 5: Layer Config.
Step 6: Simulation Control
Step 7: Probe Config.
Probing
Advanced Features
Developer Tools

The cross validation test set is used to determine the level of generalization produced by the training set. Often a network can be over trained, such that it will begin to "memorize" the training set at the expense of the test set performance. The Simulation Control panel can be configured to automatically stop the training when the error in the test set begins to rise.

Cross validation is executed in concurrence with the training of the network. After every training epoch, the network weights are frozen, the cross validation data is fed through the network, and the results are reported.

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