5 search results - page 1 / 1 » Reducing UK-Means to K-Means |
ICIC
2005
Springer
14 years 4 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 10 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 8 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 12 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
14 years 5 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...