On 01/21/2012 07:08 AM, Gilles Louppe wrote:
> Yep, I think that your solution would work Olivier. I am buzy this
> week-end but I can push a first draft of this refactoring by the
> beginning of next week.
>
That would be pretty awesome :)
Thanks for tackling this!
Cheers,
Andy
---
Yep, I think that your solution would work Olivier. I am buzy this week-end
but I can push a first draft of this refactoring by the beginning of next
week.
Gilles
On Saturday, 21 January 2012, Olivier Grisel
wrote:
> 2012/1/20 Andreas :
>> On 01/20/2012 11:07 PM, [email protected] wrote:
>>> I w
2012/1/20 Andreas :
> On 01/20/2012 11:07 PM, [email protected] wrote:
>> I wonder if the Decision Tree base estimator could derive from a more
>> general base estimator for Random Forests and just, for example, override a
>> setup method or a constructor?
>>
>>
> This seems like a very good idea
On 01/20/2012 11:07 PM, [email protected] wrote:
> I wonder if the Decision Tree base estimator could derive from a more general
> base estimator for Random Forests and just, for example, override a setup
> method or a constructor?
>
>
This seems like a very good idea.
It's definitely better
@lists.sourceforge.net
Subject: Re: [Scikit-learn-general] Ensemble meta-estimators
On 01/20/2012 10:45 PM, Gilles Louppe wrote:
> Yes indeed, as I said at the time, much of the forest code could be
> reused to implement a pure averaging meta-estimator.
>
> The main thing that makes Bas
On 01/20/2012 10:45 PM, Gilles Louppe wrote:
> Yes indeed, as I said at the time, much of the forest code could be
> reused to implement a pure averaging meta-estimator.
>
> The main thing that makes BaseForest tree-specific is that it
> precomputes X_argsorted such that it is computed only once fo
Yes indeed, as I said at the time, much of the forest code could be
reused to implement a pure averaging meta-estimator.
The main thing that makes BaseForest tree-specific is that it
precomputes X_argsorted such that it is computed only once for all
trees and inject it into the fit method of the b
2012/1/20 Andreas :
> In how far is #491 tree specific?
> This is parallelization over different boot strap samples.
> Or am I missing something there?
> Feature importance (#478) is not as generic but
> "just" relies on feature importance from the base classifier,
> right?
> Or did I miss somethin
Digging up an old thread:
>> Also, I was wondering how tree-specific the random forest module is.
>> I looked at the pull request but could not find much about this.
>> Was there any discussion on this that I missed? What was the reasoning
>> behind having mixins instread of meta-classifier for bag
Hi Andy,
On 27 December 2011 13:37, Andreas Müller wrote:
> Hi everybody!
> I was wondering if anyone is working on ensemble meta-estimators.
> There seems to have been some effort by @glouppe when doing the random
> forests.
> Is that still going on?
I am not working on that currently.
> Also,
Hi everybody!
I was wondering if anyone is working on ensemble meta-estimators.
There seems to have been some effort by @glouppe when doing the random
forests.
Is that still going on?
Also, I was wondering how tree-specific the random forest module is.
I looked at the pull request but could not f
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