On 11/15/2011 07:03 PM, Gael Varoquaux wrote:
> On Tue, Nov 15, 2011 at 05:57:14PM +, Robert Kern wrote:
>> Actually, last time I suggested it, it was brought up that the online
>> algorithms can be worse numerically. I'll try to find the thread.
> Indeed, especially for smallish datasets where
On 11/15/2011 06:02 PM, Warren Weckesser wrote:
On Tue, Nov 15, 2011 at 10:48 AM, Andreas Müller
mailto:amuel...@ais.uni-bonn.de>> wrote:
On 11/15/2011 05:46 PM, Andreas Müller wrote:
On 11/15/2011 04:28 PM, Bruce Southey wrote:
On 11/14/2011 10:05 AM, Andreas Müller
On 11/15/2011 05:46 PM, Andreas Müller wrote:
On 11/15/2011 04:28 PM, Bruce Southey wrote:
On 11/14/2011 10:05 AM, Andreas Müller wrote:
On 11/14/2011 04:23 PM, David Cournapeau wrote:
On Mon, Nov 14, 2011 at 12:46 PM, Andreas Müller
wrote:
Hi everybody.
When I did some normalization
On 11/15/2011 04:28 PM, Bruce Southey wrote:
On 11/14/2011 10:05 AM, Andreas Müller wrote:
On 11/14/2011 04:23 PM, David Cournapeau wrote:
On Mon, Nov 14, 2011 at 12:46 PM, Andreas Müller
wrote:
Hi everybody.
When I did some normalization using numpy, I noticed that numpy.std uses
more ram
On 11/14/2011 04:23 PM, David Cournapeau wrote:
> On Mon, Nov 14, 2011 at 12:46 PM, Andreas Müller
> wrote:
>> Hi everybody.
>> When I did some normalization using numpy, I noticed that numpy.std uses
>> more ram than I was expecting.
>> A quick googl
Hi everybody.
When I did some normalization using numpy, I noticed that numpy.std uses
more ram than I was expecting.
A quick google search gave me this:
http://luispedro.org/software/ncreduce
The site claims that std and other reduce operations are implemented
naively with many temporaries.
Is tha
