How to divide class in neural network for Biometric authentication?
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I just want to know how to decide class for person authentication using any of the parameter like fingerprint iris whatever. I am just eager to how to perform person authentication by Neural network as i have 5 sample for each subject i just want to train NN by 4 out of each 6 samples..
Please put you kind suggestion
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Greg Heath
il 19 Ott 2013
You are going to have to design many candidate nets to decide the number of hidden nodes and which random weight initialization will yields the best net. If you have a lot of data, you can just use the default dividerand with the default train/val/test ratio = 0.7/0.15/0.15 . However, if this isn't satisfactory, you could change it to 0.666/0.167/0.167/. However, it really isn't worth the trouble.
If you don't have much data you might want to use divideind to specify which inputs belong to each trn/val/test subset.
How many people are there? If there are Np people you could use one input from each person in every group of Np.
Hope this helps.
Greg
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