How to determine the best training examples from a dataset for NN training?

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Hi!
Neural network classification accuracy is strongly dependent on the choice of training samples. k-fold cross-validation and then averaging does not seem a good option to me. It's sometimes like teaching a kid simple things and taking an exam on the difficult problems. How can one decide the best training samples for training an NN?
Thanks in advance.

Accepted Answer

Greg Heath
Greg Heath on 21 Dec 2014
There is no standard approach. One of many approaches:
1. Standardize (zscore or mapstd)
2. Remove or modify outliers
3. Obtain multiple training set only designs via newrb and/or patternnet with 'dividetrain'
4. Remove points with more than M number of misclassifications.
Hope this helps
Thank you for formally accepting my answer
Greg

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