Would it have influence on the result if some attributes are removed? Just want 
to double check because I am not very familiar with machine learning. If  no 
impact for the result after some fields are taken out of input training data, I 
will just remove those fields because that would be simpler.  

Thank for help





________________________________
From: Roland Szabo <rol...@gmail.com>
To: Jason Williams <jwilliams4...@yahoo.co.uk>; 
scikit-learn-general@lists.sourceforge.net 
Sent: Tuesday, 13 August 2013, 6:11
Subject: Re: [Scikit-learn-general] Can Random Forest Classifer ignore specific 
fields?



Isn't it simpler to just take out the attributes you want to ignore from the 
data? 

Assuming the numpy array a contains your data and you don't want the first 
column (attribute):

a = a[:,1:]




On Tue, Aug 13, 2013 at 1:03 PM, Jason Williams <jwilliams4...@yahoo.co.uk> 
wrote:

I follow an example found on the internet 
(http://blog.yhathq.com/posts/random-forests-in-python.html) for using Random 
Forest Classifer. The result looks working. From the sample code, it looks like 
taking all attributes to train the model. But checking api 
(http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
 ) there is no description telling that what parameter can be used to ignore 
some particular fileds/ attributes. So I would like to check if any parameter 
can be used to ignore particular fields or attributes? 
>
>Thanks
>
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-- 

Roland
http://rolisz.ro/

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