Network based rule representation for knowledge discovery and predictive modelling

IEEE International Conference on Fuzzy Systems

Volumn 2015-November, Issue , 2015, Pages

  Liu, Han ^a   Gegov, Alexander ^a   Cocea, Mihaela ^a  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

Author keywords

Data Mining; If Then Rules; Knowledge Discovery; Knowledge Representation; Machine Learning; Predictive Modelling; Rule Based Classification

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPLEX NETWORKS; COMPUTATIONAL EFFICIENCY; DATA MINING; DECISION TREES; EFFICIENCY; EXPERT SYSTEMS; FUZZY SYSTEMS; KNOWLEDGE REPRESENTATION; SPEECH PROCESSING; TOPOLOGY;

COMPLEXITY ANALYSIS; DIFFERENT STRUCTURE; IF-THEN RULES; INTELLIGENT DATA MININGS; MACHINE LEARNING METHODS; PREDICTIVE MODELLING; RULE REPRESENTATION; RULE-BASED CLASSIFICATION;

LEARNING SYSTEMS;

EID: 84955406986     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZ-IEEE.2015.7337807     Document Type: Conference Paper

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