72 search results - page 1 / 15 » On Dynamic Weighting of Data in Clustering with K-Alpha Mean... |
73
Voted
ICPR
2010
IEEE
14 years 8 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...
81
Voted
ICPR
2010
IEEE
14 years 10 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
15 years 7 days 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...
87
Voted
BMCBI
2008
14 years 10 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...
108
Voted
AICCSA
2008
IEEE
15 years 8 days 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...