Hi Gilles.
Thanks! Will try that.

Also thanks for working on the docs! :)

Cheers,
Andy


On 01/03/2012 09:30 AM, Gilles Louppe wrote:
> Hi Andras,
>
> Try setting min_split=10 or higher. With a dataset of that size, there
> is no point in using min_split=1, you will 1) consume indeed too much
> memory and 2) overfit.
>
> Gilles
>
> PS: I have just started to change to doc. Expect a PR later today :)
>
> On 3 January 2012 09:27, Andreas<[email protected]>  wrote:
>    
>> Hi Brian.
>> The dataset itself is 60000 * 786 * 8 bytes (I converted from unit8 to
>> float which is 8 bytes in Numpy I guess)
>> which is ~ 360 MB (also I can load it ;).
>> I trained linear SVMs and Neural networks without much trouble. I
>> haven't really studied the
>> decision tree code (which I know you made quite an effort to optimize)
>> so I don't really
>> have an idea how the construction works. Maybe I just had a
>> misconception of the memory
>> usage of the algorithm. I just started playing with it.
>>
>> Thanks for any comments :)
>>
>> Cheers,
>> Andy
>>
>>
>> On 01/03/2012 09:06 AM, [email protected] wrote:
>>      
>>> Hi Andy,
>>>
>>> IIRC MNIST is 60000 samples, each with dimension 28x28, so the 2GB limit 
>>> doesn't seem unreasonable (especially since you don't have all of that at 
>>> your disposal). Does the dataset fit in mem?
>>>
>>> Brian
>>>
>>> -----Original Message-----
>>> From: Andreas<[email protected]>
>>> Date: Tue, 03 Jan 2012 09:00:47
>>> To:<[email protected]>
>>> Reply-To: [email protected]
>>> Subject: Re: [Scikit-learn-general] Question and comments on RandomForests
>>>
>>> One other question:
>>> I tried to run a forest on MNIST, that actually consisted of only one tree.
>>> That gave me a memory error. I only have 2gb ram in this machine
>>> (this is my desktop at IST Austria !?) which is obviously not that much.
>>> Still this kind of surprised me. Is it expected that a tree takes
>>> this "much" ram? Should I change "min_density"?
>>>
>>> Thanks :)
>>>
>>> Andy
>>>
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