Is there a description about this somewhere? I can’t find it in the docu.

Thanks!

Am 05.09.2014 um 18:40 schrieb Flavio Vinicius <[email protected]>:

> I the case of LinearRegression independent models are being fit for
> each response. But this is not the case for every multi-response
> estimator. Afaik, the multi response regression forests in sklearn
> will consider the correlation between features.
> --
> Flavio
> 
> 
> On Fri, Sep 5, 2014 at 11:03 AM, Philipp Singer <[email protected]> wrote:
>> Hey!
>> 
>> I am currently working with data having multiple outcome variables. So for 
>> example, my outcome I want to predict can be of multiple dimension. One line 
>> of the data could look like the following:
>> 
>> y = [10, 15]  x = [13, 735478, 0.555, …]
>> 
>> So I want to predict all dimensions of the outcome.
>> 
>> I have seen that some algorithms can predict such multiple targets. I have 
>> tried it with LinearRegression and it seems to work fine.
>> 
>> I have not found a clear description of how this works though. Does it fit 
>> one Regression separately for each outcome variable?
>> 
>> Best,
>> Philipp
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