That totally depends on your data. Here it looks like you are scaling down
a feature that captures a lot of the variation you are looking for, thus
making it less important with respect to the other features in the
euclidean distance. You could try selecting important features beforehand.
But they may be non-coordinate directions in your feature space as well.
Michael
On Tue, Jul 8, 2014 at 3:56 PM, Sheila the angel <from.d.pu...@gmail.com>
wrote:
> While using Nearest Neighbors Classification, I am getting higher
> cross-validation accuracy with raw data (without scaling) compare to scaled
> data (using preprocessing.scale) .
>
> Is this normal?
> When should one scale the data?
>
>
> Thanks
> --
> Sheila
>
>
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