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.
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Accepted Answer
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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