A computational framework for nonlinear dimensionality reduction and clustering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5629 LNCS, Issue , 2009, Pages 334-343

  Wismüller, Axel ^a  

^a UNIVERSITY OF ROCHESTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSICAL TOPOLOGIES; CLUSTER STRUCTURE; COMPUTATIONAL FRAMEWORK; COMPUTATIONAL SAVINGS; CONVENTIONAL APPROACH; CONVENTIONAL TOPOLOGIES; FEATURE MAPPING; FUNCTIONAL COMPONENTS; GRAPHICAL DISPLAYS; INPUT DATAS; KNOWLEDGE DISCOVERY; LARGE DATA; MAPPING ALGORITHMS; NONLINEAR DIMENSIONALITY REDUCTION; NONLINEAR EMBEDDING; SCIENTIFIC DATA; SELF-ORGANIZATIONS; STRUCTURE-PRESERVING;

CONFORMAL MAPPING; DATA ACQUISITION; DATA REDUCTION; DATA VISUALIZATION; ELECTRIC NETWORK TOPOLOGY; TOPOLOGY;

SELF ORGANIZING MAPS;

EID: 69049087809     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02397-2_38     Document Type: Conference Paper

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