On Mon, Jan 20, 2014 at 8:19 AM, Su, Jian, Ph.D. <[email protected]> wrote:
>
>
> Hi,
>
>
>
> I now know how to select features with numbers (0D), but some of the
> features are vectors (1D) or arrays (2D) or possibly higher-dimensional.
>
>
>
> For example, for object 1 we have two features:
>
> Feature #1: 1
>
> Feature #2: [2,3]
>
> And such for all other objects.
>
Hi,
The best approach will depend on your problem, but generally you can start
by separating any multi-component features into single features: i.e. in
the problem above you work as if you have three (single-component) features
for each object.
If you have some intuition about how your multi-component features may be
related, other approaches might be better. For example, if your
multi-component feature is a vector, the magnitude or direction of the
vector might be most important for your own problem, and you can choose the
features you use in your estimator to take advantage of that knowledge.
Depending on the particular estimator you use, however, this type of
feature engineering may or may not lead to better results than simply
splitting-up the compound features.
Hope that helps,
Jake
>
>
> Solutions:
>
> 1. Separate feature #2 to 2 0D features.
>
> 2. Calculate a new 0D feature from feature #2.
>
>
>
> Neither sounds valid to me.
>
>
>
> Thanks,
>
> Sukye
>
>
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