You should move to 0.8 and explore ball k-means.
On Tue, Dec 3, 2013 at 8:44 PM, Prabhakar Srinivasan
prabhakar.sriniva...@gmail.com wrote:
Hello
I am using Mahout 0.7 currently and this question is pertaining to that
version. I am using Canopy clustering (CanopyDriver class) first to
Hello!
Can someone point me to some explanatory documentation for Outlier
Detection Removal in Clustering in Mahout. I am unable to understand the
internal mechanism of outlier detection just by reading the Javadoc:
clusterClassificationThreshold Is a clustering strictness / outlier removal
Can you be more specific about which code you are asking about?
The ball k-means implementation provides a capability somewhat like this,
but perhaps in a more clearly defined way.
On Tue, Dec 3, 2013 at 9:34 AM, Prabhakar Srinivasan
prabhakar.sriniva...@gmail.com wrote:
Hello!
Can someone
On Tue, Dec 3, 2013 at 9:34 AM, Prabhakar Srinivasan
prabhakar.sriniva...@gmail.com wrote:
Hello!
Can someone point me to some explanatory documentation for Outlier
Detection Removal in Clustering in Mahout. I am unable to understand the
internal mechanism of outlier detection just by
Hello
I am using Mahout 0.7 currently and this question is pertaining to that
version. I am using Canopy clustering (CanopyDriver class) first to
determine the optimal number of clusters that best fits the dataset and
passing that information as parameter to Kmeans clustering (kmeansDriver
