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Aspects in Classification Learning - Review of Recent Developments in Learning Vector Quantization

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Classification is one of the most frequent tasks in machine learning. However, the variety of classification tasks as well as classifier methods is huge. Thus the question is coming up: which classifier is suitable for a given problem or how can we utilize a certain classifier model for different tasks in classification learning. This paper focuses on learning vector quantization classifiers as one of the most intuitive prototype based classification models. Recent extensions and modifications of the basic learning vector quantization algorithm, which are proposed in the last years, are highlighted and also discussed in relation to particular classification task scenarios like imbalanced and/or incomplete data, prior data knowledge, classification guarantees or adaptive data metrics for optimal classification.
Rocznik
Strony
79--105
Opis fizyczny
Bibliogr. 112 poz.
Twórcy
autor
  • Computational Intelligence Group at the University of Applied Sciences Mittweida, Dept. of Mathematics, Technikumplatz 17, 09648 Mittweida, Saxonia - Germany
autor
  • Computational Intelligence Group at the University of Applied Sciences Mittweida, Dept. of Mathematics, Technikumplatz 17, 09648 Mittweida, Saxonia - Germany
autor
  • Computational Intelligence Group at the University of Applied Sciences Mittweida, Dept. of Mathematics, Technikumplatz 17, 09648 Mittweida, Saxonia - Germany
autor
  • Computational Intelligence Group at the University of Applied Sciences Mittweida, Dept. of Mathematics, Technikumplatz 17, 09648 Mittweida, Saxonia - Germany
autor
  • Computational Intelligence Group at the University of Applied Sciences Mittweida, Dept. of Mathematics, Technikumplatz 17, 09648 Mittweida, Saxonia - Germany
autor
  • Computational Intelligence Group at the University of Applied Sciences Mittweida, Dept. of Mathematics, Technikumplatz 17, 09648 Mittweida, Saxonia - Germany
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Bibliografia
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