Step 2: Training the Neural Network

The following command trains the neural network with your data.

>> mynet = nsTrain (mynet, x, y);

where, x is the input data and y is the desired data.

What do Input Data and Desired Data mean?

Cross validation can be performed without any additional effort by passing the cross validation data to the train function as well.

>> mynet = nsTrain (mynet, x, y, cv_x, cv_y);

where cv_x is the cross-validation input data and cv_y is the cross-validation desired data.

What is Cross Validation?

The learning curve and the output and desired plots can be seen with ease after training by setting their respective parameters to true.

>> mynet = nsnn;
>> mynet.learningCurve = true;
>> mynet.outputAndDesired = true;
>> mynet = nsTrain (mynet, inputData, desiredData);

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