"Hole\u0148a, Martin" . . "P(1ET100300517), P(GA201/05/0325), Z(AV0Z10300504)" . "Classification of EEG Data using Fuzzy k-NN Ensembles" . "[FAE85C2FAD5D]" . . . "Classification of EEG Data using Fuzzy k-NN Ensembles"@en . . "Informa\u010Dn\u00E9 technol\u00F3gie - Aplik\u00E1cie a Te\u00F3ria" . "PONT" . "RIV/67985807:_____/07:00087505" . "2"^^ . . "Classification of EEG Data using Fuzzy k-NN Ensembles" . . "Klasifikace EEG dat s pou\u017Eit\u00EDm kombinov\u00E1n\u00ED Fuzzy k-NN klasifik\u00E1tor\u016F"@cs . . "ensemble methods; classifier combining; classifier fusion; classifier aggregation; Sugeno fuzzy integral"@en . "2"^^ . "91;94" . "2007-09-21+02:00"^^ . . "\u0160tefka, David" . "Se\u0148a" . . "Metody spojov\u00E1n\u00ED klasifik\u00E1tor\u016F se sna\u017E\u00ED zlep\u0161it kvalitu klasifikace t\u00EDm, \u017Ee pou\u017E\u00EDvaj\u00ED n\u011Bkolik r\u016Fzn\u00FDch klasifik\u00E1tor\u016F a kombinuj\u00ED jejich v\u00FDstupy. V tomto \u010Dl\u00E1nku pop\u00ED\u0161eme pou\u017Eit\u00ED tzv. ensembleov\u00FDch metod pro klasifikaci dat z projektu \u201EBudov\u00E1n\u00ED neuroinforma\u010Dn\u00EDch b\u00E1z\u00ED a z\u00EDsk\u00E1v\u00E1n\u00ED znalost\u00ED z nich\u201C, v kter\u00E9m se studuje mo\u017Enost prevence mikrosp\u00E1nk\u016F u \u0159idi\u010D\u016F. Metoda \u201Emultiple feature subset\u201C je pou\u017Eita k zv\u00FD\u0161en\u00ED kvality klasifikace pomoc\u00ED fuzzy k-NN klasifik\u00E1toru. Pro agregaci jsou pou\u017Eity dva p\u0159\u00EDstupy \u2013 st\u0159edn\u00ED hodnota a Sugen\u016Fv fuzzy integr\u00E1l, z nich\u017E lep\u0161\u00EDch v\u00FDsledk\u016F dosahuje st\u0159edn\u00ED hodnota."@cs . "4"^^ . . . . . "Ensemble methods try to improve quality of classification by creating multiple classifiers and aggregating their outputs. In this paper, we present the use of ensemble methods for classification of EEG data from the project %22Building Neuroinformation Bases, and Extracting Knowledge from them%22, within which a possibility of preventing drivers' microsleeps is studied. A multiple feature subset ensemble method is used to improve the quality of classification of a fuzzy k-nearest neighbor classifier. Two different aggregation schemes are used - the mean value aggregation algorithm outperforming the Sugeno fuzzy integral aggregation algorithm" . . . "Ensemble methods try to improve quality of classification by creating multiple classifiers and aggregating their outputs. In this paper, we present the use of ensemble methods for classification of EEG data from the project %22Building Neuroinformation Bases, and Extracting Knowledge from them%22, within which a possibility of preventing drivers' microsleeps is studied. A multiple feature subset ensemble method is used to improve the quality of classification of a fuzzy k-nearest neighbor classifier. Two different aggregation schemes are used - the mean value aggregation algorithm outperforming the Sugeno fuzzy integral aggregation algorithm"@en . . "978-80-969184-6-1" . . "Klasifikace EEG dat s pou\u017Eit\u00EDm kombinov\u00E1n\u00ED Fuzzy k-NN klasifik\u00E1tor\u016F"@cs . "413870" . "Classification of EEG Data using Fuzzy k-NN Ensembles"@en . "Po\u013Eana" . . "RIV/67985807:_____/07:00087505!RIV08-AV0-67985807" . . . . .