Note also that when using bootstrap=True, copies of X have to be
created for each tree.

But this should work anyway since you only build 1 tree... Hmmm.

Gilles

On 3 January 2012 09:41, Peter Prettenhofer
<[email protected]> wrote:
> Hi Andy,
>
> I'll investigate the issue with an artificial dataset of comparable
> size - to be honest I suspect that we focused on speed at the cost of
> memory usage...
>
> As a quick fix you could set `min_density=1` which will result in less
> memory copies at the cost of runtime.
>
> best,
>  Peter
>
> 2012/1/3 Andreas <[email protected]>:
>> 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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>
>
> --
> Peter Prettenhofer
>
> ------------------------------------------------------------------------------
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