Pruning strategies based on the upper bound of information gain for discriminative subgraph mining

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

Volumn 5465 LNAI, Issue , 2009, Pages 50-60

  Ohara, Kouzou ^a   Hara, Masahiro ^a   Takabayashi, Kiyoto ^a   Motoda, Hiroshi ^a   Washio, Takashi ^a  

^a OSAKA UNIVERSITY   (Japan)

Author keywords

Data mining; Discriminative subgraph; Graph mining; Information gain

Indexed keywords

ARTIFICIAL DATASETS; CLASS LABELS; CLASSIFICATION MODELS; DISCRIMINABILITY; DISCRIMINATIVE SUBGRAPH; GRAPH MINING; GRAPH STRUCTURED DATA; GRAPH-BASED INDUCTION; INFORMATION GAIN; PRUNING METHODS; PRUNING STRATEGY; SEARCH SPACES; SUBGRAPH; SUBGRAPH MINING; SUBGRAPHS; SUPER GRAPH; TIME AND SPACE; UPPER BOUND;

GRAPHIC METHODS; KNOWLEDGE ACQUISITION; LABELS; MERGERS AND ACQUISITIONS; MINING;

DATA MINING;

EID: 67650248676     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01715-5_5     Document Type: Conference Paper

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