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
2013-10-19
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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