[scikit-learn] How is linear regression in scikit-learn done? Do you need train and test split?

[Nicolas Hug]

Splitting the data into train and test data is needed with any machine 
learning model (not just linear regression with or without least squares).

The idea is that you want to evaluate the performance of your model 
(prediction + scoring) on a portion of the data that you did not use for 
training.

You'll find more details in the user guide 
https://scikit-learn.org/stable/modules/cross_validation.html

Nicolas


On 5/31/19 8:54 PM, C W wrote:
> Hello everyone,
>
> I'm new to scikit learn. I see that many tutorial in scikit-learn 
> follows the work-flow along the lines of
> 1) tranform the data
> 2) split the data: train, test
> 3) instantiate the sklearn object and fit
> 4) predict and tune parameter
>
> But, linear regression is done in least squares, so I don't think 
> train test split is necessary. So, I guess I can just use the entire 
> dataset?
>
> Thanks in advance!
>
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