Data splitting for artificial neural networks using SOM-based stratified sampling

Neural Networks

Volumn 23, Issue 2, 2010, Pages 283-294

  May, R J ^a   Maier, H R ^b   Dandy, G C ^b  

^a United Water International   (Australia)

^b UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Artificial neural networks; Cross validation; Data splitting; Self organizing maps; Stratified sampling

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BIAS AND VARIANCE; CROSS VALIDATION; DATA SETS; DATA SPLITTING; ERROR SAMPLING; FUNCTION APPROXIMATION; HIGH QUALITY; LARGE DATASETS; MODEL PERFORMANCE; NONUNIFORM; RANDOM SAMPLING; SAMPLE SIZES; STATISTICAL DIFFERENCES; STRATIFIED SAMPLING; VARIABLE MODEL;

CONFORMAL MAPPING; SELF ORGANIZING MAPS; STRENGTH OF MATERIALS;

SAMPLING;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; METHODOLOGY; PRIORITY JOURNAL; SAMPLE SIZE; SAMPLING; STATISTICAL ANALYSIS; VALIDATION PROCESS;

ALGORITHMS; CLUSTER ANALYSIS; DATABASES AS TOPIC; DATABASES, FACTUAL; LEARNING; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS;

EID: 74149090502     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2009.11.009     Document Type: Article

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