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Suggestion for cleaner normalization implementation #117

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ychong opened this issue Jan 29, 2018 · 1 comment
Open

Suggestion for cleaner normalization implementation #117

ychong opened this issue Jan 29, 2018 · 1 comment
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@ychong
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ychong commented Jan 29, 2018

Hi,

If it's not too much, I have a suggestion for a cleaner implementation of x_vals normalization.

Instead of defining a separate function, and since the objective of normalization is just to allow for faster convergence, we could perform the following:

x_vals_train = x_vals_train / x_vals_train.max(axis=0)
x_vals_test = x_vals_test / x_vals_test.max(axis=0)

This implementation is cleaner and achieve similar loss results. Do let me know what you think.

Sincerely,
Yi Xiang
chongyixiang@gmail.com

@nfmcclure
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I'll look into this. Thanks!

@nfmcclure nfmcclure self-assigned this Mar 21, 2018
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