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» A Method for Dynamic Clustering of Data
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JMLR
2010
225views more  JMLR 2010»
14 years 6 months ago
Hartigan's Method: k-means Clustering without Voronoi
Hartigan's method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuri...
Matus Telgarsky, Andrea Vattani
TIME
1997
IEEE
15 years 4 months ago
On Effective Data Clustering in Bitemporal Databases
Temporal databases provide built-in supports for efficient recording and querying of time-evolving data. In this paper, data clustering issues in temporal database environment are...
Jong Soo Kim, Myoung-Ho Kim
ACSW
2004
15 years 1 months ago
Clustering Stream Data by Regression Analysis
In data clustering, many approaches have been proposed such as K-means method and hierarchical method. One of the problems is that the results depend heavily on initial values and...
Masahiro Motoyoshi, Takao Miura, Isamu Shioya
BMCBI
2006
186views more  BMCBI 2006»
14 years 12 months ago
Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
Xiaoli Li, Yin-Chet Tan, See-Kiong Ng
PRL
2006
77views more  PRL 2006»
14 years 11 months ago
Wavelet based approach to cluster analysis. Application on low dimensional data sets
In this paper, we present a wavelet based approach which tries to automatically find the number of clusters present in a data set, along with their position and statistical proper...
Xavier Otazu, Oriol Pujol