normalization for neural network
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need clarification on normalization.
I have 3 inputs (with different units), 1 output and a total of 27 samples. 21 samples will be used for training and another 6 samples for testing. my inputs and output is not in range 0 to 1. so i need to normalize it.my questions is
Do i need to normalize it by column or row or input/output? let say, here are the first 3 samples of inputs and outputs
- inputs >> output
- 3 45 -10 >> 3
- 5 55 -3 >> 56
- 6 23 -4 >> 32
*note that all 3 inputs are in different units
so, do i need to normalize by row (3 45 -10) or by column (3 5 6) or using all inputs [3 45 -10; 5 55 -3; 6 23 -4] without considering the units at the same time?
i want to normalize in 0.1-0.9 range. can i used mapminmax?
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Greg Heath
2013-5-30
0 个投票
All of the current NN designs use mapminmax by default. However, for purposes of understanding, I use zscore (you can use mapstd) for pre-training analysis and plotting. For convenience, I let the design function use the default mapminmax just because it is a pain to remove it.
There is absolutely no reason whatsoever to use 0.1-0.9.
Why would you want to normalize columns???
Hope this helps.
Thank you for formally accepting my answer
Greg
2 个评论
azie
2013-6-11
Greg Heath
2013-6-17
To use the NNTBX, variables are rows, and samples are columns. Normalize each variable row according to its own summary stats.
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