On Thu, Apr 05, 2012 at 01:05:01PM -0700, Abhishek Pratap wrote:
> Also in my case I dont really have a good approximate on value of K in
> K-means.
That's a hard problem, for which I have no answer, sorry :$
G
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Also in my case I dont really have a good approximate on value of K in K-means.
-A
On Thu, Apr 5, 2012 at 8:06 AM, Abhishek Pratap wrote:
> Hi Gael
>
> The MemoryError exception I am getting is from using scikit's DBSCAN
> implementation. I can check mini-batch implementation of Kmeans.
>
> Best
Hi Gael
The MemoryError exception I am getting is from using scikit's DBSCAN
implementation. I can check mini-batch implementation of Kmeans.
Best,
-Abhi
On Wed, Apr 4, 2012 at 10:33 PM, Gael Varoquaux
wrote:
> On Wed, Apr 04, 2012 at 04:41:51PM -0700, Abhishek Pratap wrote:
>> Thanks Chris. So
On Wed, Apr 04, 2012 at 04:41:51PM -0700, Abhishek Pratap wrote:
> Thanks Chris. So I guess the question becomes how can I efficiently
> cluster 1 million x,y coordinates.
Did you try the scikit-learn's implementation of DBSCAN:
http://scikit-learn.org/stable/modules/clustering.html#dbscan
? I am
Thanks Chris. So I guess the question becomes how can I efficiently
cluster 1 million x,y coordinates.
-Abhi
On Wed, Apr 4, 2012 at 4:35 PM, Chris Barker wrote:
> On Wed, Apr 4, 2012 at 4:17 PM, Abhishek Pratap
>> close to a 900K points using DBSCAN algo. My input is a list of ~900k
>> tuples ea
On Wed, Apr 4, 2012 at 4:17 PM, Abhishek Pratap
> close to a 900K points using DBSCAN algo. My input is a list of ~900k
> tuples each having two points (x,y) coordinates. I am converting them
> to numpy array and passing them to pdist method of
> scipy.spatial.distance for calculating distance betw
Hey Guys
I am new to both python and more so to numpy. I am trying to cluster
close to a 900K points using DBSCAN algo. My input is a list of ~900k
tuples each having two points (x,y) coordinates. I am converting them
to numpy array and passing them to pdist method of
scipy.spatial.distance for ca
