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» Discriminative K-means for Clustering
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NN
2006
Springer
127views Neural Networks» more  NN 2006»
13 years 7 months ago
Assessing self organizing maps via contiguity analysis
- Contiguity Analysis is a straightforward generalization of Linear Discriminant Analysis in which the partition of elements is replaced by a more general graph structure. Applied ...
Ludovic Lebart
PAMI
2012
11 years 10 months ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre
WEBDB
2007
Springer
162views Database» more  WEBDB 2007»
14 years 1 months ago
Term Ranking for Clustering Web Search Results
Clustering web search engine results for ambiguous keyword searches poses unique challenges. First, we show that one cannot readily import the frequency based feature ranking to c...
Fatih Gelgi, Hasan Davulcu, Srinivas Vadrevu
ESWS
2008
Springer
13 years 9 months ago
Conceptual Clustering and Its Application to Concept Drift and Novelty Detection
Abstract. The paper presents a clustering method which can be applied to populated ontologies for discovering interesting groupings of resources therein. The method exploits a simp...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
DICTA
2007
13 years 9 months ago
K-means Clustering for Classifying Unlabelled MRI Data
Texture analysis of the liver for the diagnosis of cirrhosis is usually region-of-interest (ROI) based. Integrity of the label of ROI data may be a problem due to sampling. This p...
Gobert N. Lee, Hiroshi Fujita