MATLAB: Confusion matrix neural network plot interpretation

confusion plotneural nets

I would greatly appreciate if someone could help me interpret the confusion matrix below. I don't understand the red, green and grey boxes.Also, what is the difference between test, validation, training and all confusion matrix. Thanks in advance!

Best Answer

By default, the data is divided into three subsets (trn/val/tst):
total = training + validation + testing
You can think of it two different ways:
1. total      = designing + testing
   designing  = training + validation
2. total      = training + nontraining
  nontraining = validation + testing
TRAINING SUBSET: Design data used to directly determine the weights and thresholds of the model given inputs and targets (desired outputs). It's performance estimates are, obviously, highly biased.
VALIDATION SUBSET: Nontraining design data used two ways:
1. Validation stopping: Training is stopped 
   when the error on the validation subset  
   increases for 6(default) consecutive epochs.
2. Ranking multiple designs with slightly 
   biased performance estimates that typically 
   differ by 
   a. number of hidden nodes  
   b. initial random weight assignments.
TESTING SUBSET: Once designs are ranked to be satisfactory, UNBIASED PERFORMANCE ESTIMATES are obtained using the test subset.
 If no unbiased performance estimate is 
 satisfactory, the process can be repeated with 
 the data repartitioned and/or design parameters 
 changed.
MATLAB yields separate confusion matrices for the three data division subsets in addition to the one for all of the data .
Hope this helps.
Greg
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