[scikit-learn] Is there regression algo with 3-d input?

[Stuart Reynolds]

Would the output be different if you simply wrapped the whole process with
reshaping 3D input to 2d?

On Wed, Dec 5, 2018 at 7:14 PM lampahome <pahome.chen at mirlab.org> wrote:

> I want to regress time series prediction per week, so the unit of train
> data X is the day ex: Mon, Tue, Wed...etc.
>
> Ex: train data X is like below
> X:
> [ [1,2,3,4,3,2,1]
>  ,[2,2,3,4,3,2,2]  ]
> Each data of each row is about the day of one week. So each row has 7 data.
>
> Now if I have another feature W in each day like weather, or traffic or
> else.
>
> I thought expand the X to 3d is reasonable because the W should be
> contained in each day in X.
>
> So what I thought X is:
> [ [ [1, W-Mon], [2, W-Tue]  , [3, W-Wed]  , [4, W-Thu]  , [3, W-Fri]  ,
> [2, W-Sat]  , [1, W-Sun]  ]
> , [ [2, W-Mon], [2, W-Tue]  , [3, W-Wed]  , [4, W-Thu]  , [3, W-Fri]  ,
> [2, W-Sat]  , [2, W-Sun]  ]   ]
> It become a 3d input and contain every feature of each day.
>
> Does scikit have regression algo can accept the 3d input X ?
> I almost found algo can only accept 2d input X ex: *X* : array-like or
> sparse matrix, shape = [n_samples, n_features]
>
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20181205/3b87ebf7/attachment.html>