2012/4/13 Conrad Lee <[email protected]>:
> Thanks for the suggestion of how to change RFE.py to exploit warm_start.
> Should I add this feature to rfe.py and make a pull request?  Or is this
> functionality too specialized?
>
>> As we said in the issue you opened recently, SGDRegressor doesn't monitor
>> convergence therefore warm_start won't make things faster out of the box.
>> But you can still try to reduce the number of iterations by hand (since the
>> solution is warm-started, you can expect SGD to find a solution in a fewer
>> iterations).
>
>
> Do you know of other fast estimators I can use that do check for
> convergence?  Or is SGDRegressor in general the fastest?  I know speed will
> depend on many factors, what other estimators would you suggest as quite
> quick?

``benchmarks/bench_sgd_regressor.py`` illustrates the effect of number
of training samples and number of features on the training time of
different regressors.

It seems that SGDRegressor excels in the large n regime - below 1000
samples, Ridge should be faster. Please take the results with a grain
of salt - I bet I spent more time on tuning SGDRegressor than the
others....

best,
 Peter

>
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-- 
Peter Prettenhofer

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