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SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
13 years 6 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
DMIN
2009
119views Data Mining» more  DMIN 2009»
13 years 5 months ago
Abnormal Process State Detection by Cluster Center Point Monitoring in BWR Nuclear Power Plant
This paper proposes a new method to detect abnormal process state. The method is based on cluster center point monitoring in time and is demonstrated in its application to data fro...
Jaakko Talonen, Miki Sirola
ICDM
2009
IEEE
147views Data Mining» more  ICDM 2009»
13 years 5 months ago
Greedy Optimization for Contiguity-Constrained Hierarchical Clustering
The discovery and construction of inherent regions in large spatial datasets is an important task for many research domains such as climate zoning, eco-region analysis, public heal...
Diansheng Guo
ISBI
2011
IEEE
12 years 11 months ago
3D elastic registration improves HARDI-derived fiber alignment and automated tract clustering
High angular resolution diffusion imaging (HARDI) allows population studies of fiber integrity and connectivity. Tractography can extract individual fibers. For group studies, fib...
Yan Jin, Yonggang Shi, Neda Jahanshad, Iman Aganj,...
ECML
2007
Springer
14 years 2 months ago
Generalization-Based Similarity for Conceptual Clustering
The availability of techniques for comparing descriptions has many applications in Artificial Intelligence, ranging from description selection to flexible matching, from instance...
Stefano Ferilli, Teresa Maria Altomare Basile, Nic...