72 search results - page 1 / 15 » On Dynamic Weighting of Data in Clustering with K-Alpha Mean... |
ICPR
2010
IEEE
13 years 3 months ago
2010
IEEE
Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a...
ICPR
2010
IEEE
13 years 5 months ago
2010
IEEE
The conventional mean shift algorithm has been known to be sensitive to selecting a bandwidth. We present a robust mean shift algorithm with heterogeneous node weights that come f...
CIKM
2006
Springer
13 years 7 months ago
2006
Springer
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
BMCBI
2008
13 years 5 months ago
2008
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
AICCSA
2008
IEEE
13 years 7 months ago
2008
IEEE
Data grids deal with a huge amount of data regularly. It is a fundamental challenge to ensure efficient accesses to such widely distributed data sets. Creating replicas to a suita...