A Bayes-true data generator for evaluation of supervised and unsupervised learning methods

Pattern Recognition Letters

Volumn 32, Issue 11, 2011, Pages 1523-1531

  Frasch, Janick V ^a,b   Lodwich, Aleksander ^a   Shafait, Faisal ^a   Breuel, Thomas M ^b  

^a GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

^b Rheinland Pfälzische Technische Universität Kaiserslautern Landau   (Germany)

Author keywords

Benchmarking; Experimental proofs; Synthetic data generation

Indexed keywords

DATA MINING METHODS; EXPERIMENTAL PROOFS; FEATURE DOMAIN; LARGE DATASETS; PERFORMANCE EVALUATION; PROBLEM DOMAIN; REAL WORLD DATA; STATISTICAL LEARNING METHODS; STATISTICAL PROPERTIES; SYNTHETIC DATA; UNSUPERVISED LEARNING METHOD;

BENCHMARKING; EXPERIMENTS; PATTERN RECOGNITION; UNSUPERVISED LEARNING; VIRTUAL REALITY;

REAL VARIABLES;

EID: 79957458355     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2011.04.010     Document Type: Article

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