Hi Maheshakya,
It's probably right: your feature space is too big and sparse to be
reasonable for random forests. What sort of categorical data are you
encoding? What is the shape of the matrix after applying one-hot encoding?
If you need to use random forests, and not a method that natively handles
sparse data better, you will almost certainly need to reduce your feature
space one way or another.
- Joel
On Thu, Jun 20, 2013 at 11:19 PM, Maheshakya Wijewardena <
pmaheshak...@gmail.com> wrote:
> The shape is (32769, 8). There are 8 categorical variables before applying
> OneHotEncoding.
>
>
> On Thu, Jun 20, 2013 at 5:43 PM, Peter Prettenhofer <
> peter.prettenho...@gmail.com> wrote:
>
>>
>> Hi,
>>
>> seems like your sparse matrix is too large to be converted to a dense
>> matrix. What shape does X have? How many categorical variables do you have
>> (before applying the OneHotTransformer)?
>>
>>
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