5 search results - page 1 / 1 » Reducing UK-Means to K-Means |
ICIC
2005
Springer
13 years 10 months ago
2005
Springer
This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
TKDE
2008
13 years 4 months ago
2008
Given a dataset P, a k-means query returns k points in space (called centers), such that the average squared distance between each point in P and its nearest center is minimized. S...
FOCS
2010
IEEE
13 years 2 months ago
2010
IEEE
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...
ICPR
2004
IEEE
14 years 5 months ago
2004
IEEE
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...