is my neural network properly trained ?

Hello i have a feature vector of 12455x400 matrix and out put target of 40x400 matrix .I am training using patternent and fucntion is trainscg for face recognition using local binary pattern. I hve 400 images which have 40 individuals in them. This is my neural network output .

8.333 mis classifications means it had identified almost all other ~92% of images in the test set of 60 images?

Answer 1

[Greg Heath]

Yes.

However, isn't there any way to use feature extraction to reduce your input dimension below 12455 ???

Can patternnet really handle vectors that long?

Thank you for formally accepting my answer

Greg

[Newman]

Sir I always thought that larger the dimension of the input better the classification or is it the opposite ?

[Greg Heath]

Inputs that can be approximated by combinations of other inputs should be removed.

In particular, it is those that can be approximated by LINEAR combinations of other inputs that cause the most trouble.

Typically, the larger the number of known input/output PAIRS the better the classification.

 Hope this helps.

Thank you for formally accepting my answer

 Greg

[Newman]

Sir how to find out those kind of inputs ? Do u know of any filtering techniques for the feature vector ? Or is it done manually.