mont Road, Building Two, Suite 400 | Atlanta,
> GA 30305
>
>
>
>
> -Original Message-
> From: Arnaud Joly [mailto:a.j...@ulg.ac.be]
> Sent: Thursday, October 15, 2015 7:29 AM
> To: scikit-learn-general@lists.sourceforge.net
> Subject: Re: [Scikit-learn-general]
neral] Utility of random_state parameter for
decision trees
Your intuition is correct. For a decision tree with max_feature=None, the
random_state is used to break ties randomly.
Cheers,
Arnaud
> On 14 Oct 2015, at 17:33, Kevin Markham wrote:
>
> Hello,
>
> I'm a data sci
Your intuition is correct. For a decision tree with max_feature=None, the
random_state is used to break ties randomly.
Cheers,
Arnaud
> On 14 Oct 2015, at 17:33, Kevin Markham wrote:
>
> Hello,
>
> I'm a data science instructor that uses scikit-learn extensively in the
> classroom. Yesterda
Hi Kevin.
The trees have a "max_features" parameter, that limits the number of
features used in each split.
This is not usually used in single decision trees, but rather in random
forests.
If using "max_features", then "random_state" is used to select which
features are used in each split.
I
