taraining error when neural network training is done .each time training isd one the results are different
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i am doing neural network ,training the netwrk eah time gives different results.
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Accepted Answer
Greg Heath
on 3 Dec 2012
Training performance varies because the default train/val/test data division AND initial weights are pseudorandom.
One of many solutions for sufficiently large data sets.
1. Initialize the RNG so that the same stream of pseudorandom numbers can be repeated.
rng(0)
2. Design 10 or more nets
3. Choose the net with the smallest validation (NOT TRAINING) set error.
4. Estimate the performance on unseen data with the test set error.
5. If performance is unsatisfactory, try increasing the number of hidden nodes.
How large are X and T?
Hope this helps.
Thank you for formally accepting my answer
Greg
3 Comments
Greg Heath
on 7 Dec 2012
The pseudo random number generation is done automatically. However if you want to duplicate your run(s). You must intialize the geneator.
help rng
doc rng
Greg
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