I suspect this method is underreported by any particular name, as it's a
straightforward greedy search. It is also very close to what I think many
researchers do in system development or report in system analysis, albeit
with more automation.
In the case of KNN, I would think metric learning could
Maybe we would want mrmr first?
http://penglab.janelia.org/proj/mRMR/
On 04/27/2015 06:46 PM, Sebastian Raschka wrote:
>> I guess that could be done, but has a much higher complexity than RFE.
> Oh yes, I agree, the sequential feature algorithms are definitely
> computationally more costly.
>
>
> I guess that could be done, but has a much higher complexity than RFE.
Oh yes, I agree, the sequential feature algorithms are definitely
computationally more costly.
> It seems interesting. Is that really used in practice and is there any
> literature evaluating it?
I am not sure how often
That is like a one-step look-ahead feature selection?
I guess that could be done, but has a much higher complexity than RFE.
RFE works for anything that returns "importances", not just linear models.
It doesn't really work for KNN, as you say. [I wouldn't say
non-parametric models. Trees are prett
