Beyond trees: Adopting MITI to learn rules and ensemble classifiers for multi-instance data

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

Volumn 7106 LNAI, Issue , 2011, Pages 41-50

  Bjerring, Luke ^a   Frank, Eibe ^a  

^a UNIVERSITY OF WAIKATO   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARK DATASETS; CLASSIFICATION ACCURACY; EFFECT OF PARAMETERS; ENSEMBLE CLASSIFIERS; POSITIVE EXAMPLES; PRIORITY QUEUES; RANDOMIZED ALGORITHMS; RULE LEARNERS; SIMPLE MODIFICATIONS; SPLITTING CRITERION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DECISION TREES; FORESTRY;

TREES (MATHEMATICS);

ALGORITHMS; CLASSIFICATION; DECISION THEORY; FORESTRY; INFORMATION RETRIEVAL; MATHEMATICS; TREES;

EID: 83755194948     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-25832-9_5     Document Type: Conference Paper

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