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» Algorithms for Clustering Data
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EUROPAR
2001
Springer
14 years 21 days ago
Experiments in Parallel Clustering with DBSCAN
We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a...
Domenica Arlia, Massimo Coppola
APBC
2004
121views Bioinformatics» more  APBC 2004»
13 years 9 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...
CSDA
2008
91views more  CSDA 2008»
13 years 8 months ago
Model-based clustering for longitudinal data
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
Rolando De la Cruz-Mesía, Fernando A. Quint...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
ICCV
2007
IEEE
14 years 10 months ago
Mode-seeking by Medoidshifts
We present a nonparametric mode-seeking algorithm, called medoidshift, based on approximating the local gradient using a weighted estimate of medoids. Like meanshift, medoidshift ...
Yaser Sheikh, Erum A. Khan, Takeo Kanade