Identifying fewer key factors by attribute selection methodologies to understand the hospital admission prediction pattern with Ant Miner and C4.5

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

Volumn 5712 LNAI, Issue PART 2, 2009, Pages 853-860

  Fukuda, Kyoko ^a  

^a UNIVERSITY OF CANTERBURY   (New Zealand)

Author keywords

Air pollution; Ant Miner; Attribute Selection; Hospital admission

Indexed keywords

ATTRIBUTE SELECTION; CLASSIFICATION ACCURACY; COST EFFECTIVE; DATA COLLECTION; DATA PREPROCESSING; DATA SETS; ENVIRONMENTAL SCIENCE DATA; HOSPITAL ADMISSION; HOSPITAL ADMISSIONS; KEY FACTORS; MANAGEMENT PROCESS; PREDICTION ACCURACY; TREE NODES;

AIR QUALITY; DATA PROCESSING; HOSPITALS; KNOWLEDGE BASED SYSTEMS; KNOWLEDGE ENGINEERING;

MINERS;

EID: 70849114739     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04592-9_106     Document Type: Conference Paper

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