An ensemble ofk-nearest neighbours algorithm for detection of Parkinson's disease

DOI10.1080/00207721.2013.809613zbMath1362.92029OpenAlexW2065813866MaRDI QIDQ5252899

Murat Gok

Publication date: 3 June 2015

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2013.809613

zbMATH Keywords

learning algorithmsfeature selectionParkinson's disease\(k\)-nearest neighbourensemble classificationrotation forest

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)

Related Items (2)

An intelligent Parkinson's disease diagnostic system based on a chaotic bacterial foraging optimization enhanced fuzzy KNN approach ⋮ MSEBAG: a dynamic classifier ensemble generation based on ‘minimum-sufficient ensemble' and bagging

Cites Work

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• Ensemble classification based on generalized additive models
• Bayesian network classifiers
• 10.1162/153244303322753616
• Classification of Parkinson's disease using feature weighting method on the basis of fuzzy C-means clustering
• Gene selection for cancer classification using support vector machines

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