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Re: Training multiple data for a single feedforwardnet
Posted:
Nov 17, 2012 5:27 AM
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"Carlos Aragon" wrote in message <k86qo1$1vl$1@newscl01ah.mathworks.com>...
> Greg,
>
> During this week i've been in an exhaust mood to train the neural net. I want to know how could i validate the trained neural network simulating with sim(net,P(test))
You are using incorrect terminology.
ASSUMPTION: Training, Validation and Test data can be assumed to be
random draws from the same probability distribution.
TRAINING: Used to estimate weight/bias values
VALIDATION(1): Used during training to determine when overtraining an overfit net begins
to degenerate the ability to generalize to nontraining data.
VALIDATION(2): Used after training to rank multiple designs
TEST: Used last to estimate performance on unseen data
considering that the matrix P(test) does not have the same size as the input. is it possible? How?
> Every time when i try to simply validate a test input matrix with a differente size i get an error.
If you train a net with node topology I-H-O, the size of any input/target pair must have the form
size(input) = [ I N ]
size(target) = [ O N ]
The resulting output will have the same size as the target.
If you apply the net to unknown data with or without a known target matrix, the input/output pair nust have the form
size(newinput) = [ I Nnew]
size(newoutput) = [ O Nnew]
Hope this helps.
Greg
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