> Thanks for your reply. So this mean I should start with e.g. "max_depth":
> [1,4,10,15], "min_samples_leaf":[1,10,20,30]. and if the max_depth=10 and
> min_samples_leaf=10, then I should explore values close to these values. Am I
> right?
Yes, this would work. However, keep in mind that you may be missing a "good"
combination this way. And if you have a large number of n_estimators, tuning a
random forest can be "relatively" expensive. Plus, you'd typically don't want
or need to prune the trees here, that's basically the whole idea behind RF.
> Shall I use small value of number of estimator, while conducting this
> parametric study.After that I can use a higher value while fitting my model?
Also here, the parameters that you tuned may only be good for the model based
on the specific number of estimators. In general, I would maybe advice against
tuning the hyperparameters at all and use the computational time to increase
the number of n_estimators.
> On Jan 29, 2016, at 4:18 PM, muhammad waseem <m.waseem.ah...@gmail.com> wrote:
>
> Hi Sebastian,
> Thanks for your reply. So this mean I should start with e.g. "max_depth":
> [1,4,10,15], "min_samples_leaf":[1,10,20,30]. and if the max_depth=10 and
> min_samples_leaf=10, then I should explore values close to these values. Am I
> right?
>
> Shall I use small value of number of estimator, while conducting this
> parametric study.After that I can use a higher value while fitting my model?
> Will this change other parameters, meaning is n_estimator depends on other
> parameters?
>
> Also, should I use early stopping while doing GridSearchCV?
>
> Thanks again.
> Regards
> Waseem
>
> On Fri, Jan 29, 2016 at 6:57 PM, Sebastian Raschka <se.rasc...@gmail.com
> <mailto:se.rasc...@gmail.com>> wrote:
> Hi, Waseem,
> with a fine-enough grid, the GridSearchCV would be more "thorough" than the
> randomized search. However, the problem is essentially some sort of
> combinatorial explosion. Typically, I start with a "rougher" grid (the
> different parameters are more "spaced out" relative to each other). After
> that, I use a "finer" grid around the parameters that came up in the previous
> search.
> However, it all comes down to computational time vs. being thorough. Or in
> other words, grid search is an exhaustive search whereas randomized search is
> a computationally "more efficient" approach.
>
>
> > On Jan 29, 2016, at 11:45 AM, muhammad waseem <m.waseem.ah...@gmail.com
> > <mailto:m.waseem.ah...@gmail.com>> wrote:
> >
> > Hello All,
> > I am new to scikitlearn and ML, and trying to train my model using random
> > forest and gradient boosting trees regressors. I was wondering what is the
> > best way to do hyperparameter tuning, shall I use GridSearchCV or
> > RandomisedSearchCV? I have read that the performance of RandomiseSeacrhCV
> > is almost same as GridSearchCV (most of the times). If I go with
> > RandomisedSearchCV then what should be the range of values for different
> > parameters? How will I know that the range I am selecting is the correct
> > one?
> >
> > Also, what about the number of estimators? In the GridSearchCV or
> > RandomisedSearchCV, shall I start with a low value and then after selecting
> > other parameters, I will choose a large number of estimators for fitting
> > purposes. Am I right?
> >
> > Shall I always use early stopping, no matter if I use Grid search or
> > Randomised Search?
> >
> > P.S: Training data: Number of Inputs = 6
> > Number fo Outputs = 1
> > Number of samples (rows) = 8526
> > testing data: Number of samples (rows) = 1416
> >
> > Thanks
> > Kindest Regards
> > Waseem
> > ------------------------------------------------------------------------------
> > Site24x7 APM Insight: Get Deep Visibility into Application Performance
> > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
> > Monitor end-to-end web transactions and take corrective actions now
> > Troubleshoot faster and improve end-user experience. Signup Now!
> > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________
> >
> > <http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________>
> > Scikit-learn-general mailing list
> > Scikit-learn-general@lists.sourceforge.net
> > <mailto:Scikit-learn-general@lists.sourceforge.net>
> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> > <https://lists.sourceforge.net/lists/listinfo/scikit-learn-general>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
> <http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140>
> _______________________________________________
> Scikit-learn-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> <mailto:Scikit-learn-general@lists.sourceforge.net>
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> <https://lists.sourceforge.net/lists/listinfo/scikit-learn-general>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________
> Scikit-learn-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
Site24x7 APM Insight: Get Deep Visibility into Application Performance
APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
Monitor end-to-end web transactions and take corrective actions now
Troubleshoot faster and improve end-user experience. Signup Now!
http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
