Minimum message length criterion for second-order polynomial model discovery

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

Volumn 1805, Issue , 2000, Pages 40-48

  Rumantir, Grace W ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

Automated modeUing; Scientific discovery; Second order polynomial regression

Indexed keywords

POLYNOMIALS;

AUTOMATED MODEUING; CAUSAL RELATIONSHIPS; INDEPENDENT VARIABLES; MINIMUM MESSAGE LENGTHS; MODEL SELECTION CRITERIA; SCIENTIFIC DISCOVERY; SECOND-ORDER POLYNOMIAL; SELECTION CRITERIA;

DATA MINING;

EID: 84942778115     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45571-x_7     Document Type: Conference Paper

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