Automatic classifier selection for non-experts

• Published in: Pattern analysis and applications : PAA Vol. 17; no. 1; pp. 83 - 96
• Main Authors: Reif, Matthias, Shafait, Faisal, Goldstein, Markus, Breuel, Thomas, Dengel, Andreas
• Format: Journal Article
• Language: English
• Published: London Springer London 01.02.2014; Springer
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Computer Science; Computer science; control theory; systems; Data processing. List processing. Character string processing; Exact sciences and technology; Memory organisation. Data processing; Pattern Recognition; Software; Theoretical Advances; Theoretical computing; Regression; Classifier recommendation; Classifier selection; Meta-features; Meta-learning; Landmarking; High performance; Data analysis; Automatic classification; Automatic selection; Metadata; Pattern recognition; Data mining; Open source software; Recommendation; Open systems; Learning algorithm

Choosing a suitable classifier for a given dataset is an important part of developing a pattern recognition system. Since a large variety of classification algorithms are proposed in literature, non-experts do not know which method should be used in order to obtain good classification results on the...