Re: Random Forest model (number of trees)

Thank you Peter, very nice explanation.

In some literature, I read that the 'mtry' parameter of RF is sqrt(number
of features) for classification problems and number of features / 3 for
regression problems.

Kind regards

On Wed, Apr 28, 2021 at 12:32 AM Peter Reutemann <[email protected]>
wrote:

> > I am sorry but I did not understand your point. In the more option, I
> can see
> >
> > numFeatures -- Sets the number of randomly chosen attributes. If 0,
> > int(log_2(#predictors) + 1)
> >
> > but how can I get the number of variables for each node? I have 20
> features in my dataset.
>
> #predictors is the number of attributes without the class. If you have
> 20 features incl the class, then you get:
> int(log_2(19)+1) = 5
>
> Broken down:
> log_2(19) ~ 4.25
> log_2(19) + 1 ~ 5.25
> int(log_2(19)+1) = 5
>
> That's the number of attributes that are randomly chosen for a tree in
> RandomForest.
>
> Cheers, Peter
> --
> Peter Reutemann
> Dept. of Computer Science
> University of Waikato, NZ
> +64 (7) 577-5304
> http://www.cms.waikato.ac.nz/~fracpete/
> http://www.data-mining.co.nz/
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