. "978-989-8111-66-1" . . . "classifier aggregation; classifier combining; classification confidence"@en . . "Hole\u0148a, Martin" . "6"^^ . . . . "RIV/67985807:_____/09:00320925" . . "Agregace klasifik\u00E1tor\u016F je metoda pro zv\u00FD\u0161en\u00ED kvality klasifikace. M\u00EDsto pou\u017Eit\u00ED jednoho klasifik\u00E1toru je sestaven t\u00FDm klasifik\u00E1tor\u016F a v\u00FDstupy jednotliv\u00FDch klasifik\u00E1tor\u016F jsou agregov\u00E1ny do fin\u00E1ln\u00ED predikce. V tomto p\u0159\u00EDsp\u011Bvku zkoum\u00E1me potenci\u00E1l vyu\u017Eit\u00ED m\u011Br lok\u00E1ln\u00ED konfidence klasifikace v metod\u00E1ch pro agregaci klasifik\u00E1tor\u016F. Uv\u00E1d\u00EDme dv\u011B agrega\u010Dn\u00ED metody vyu\u017E\u00EDvaj\u00EDc\u00ED lok\u00E1ln\u00ED konfidenci klasifikace a porovn\u00E1me je s dv\u011Bma b\u011B\u017En\u011B pou\u017E\u00EDvan\u00FDmi metodami pro agregaci klasifik\u00E1tor\u016F. V\u00FDsledky experiment\u016F na 4 um\u011Bl\u00FDch a 5 re\u00E1ln\u00FDch datov\u00FDch mno\u017Ein\u00E1ch ukazuj\u00ED, \u017Ee pou\u017Eit\u00ED lok\u00E1ln\u00ED konfidence klasifikace v agregaci klasifik\u00E1tor\u016F m\u016F\u017Ee signifikantn\u011B zv\u00FD\u0161it kvalitu klasifikace."@cs . "P(1ET100300517), Z(AV0Z10300504)" . "Set\u00FAbal" . "307242" . "INSTICC" . "Classifier aggregation is a method for improving quality of classification. Instead of using just one classifier, a team of classifiers is created, and the outputs of the individual classifiers are aggregated into the final prediction. In this paper, we study the potential of using measures of local classification confidence in classifier aggregation methods. We introduce four measures of local classification confidence and study their suitability for classifier aggregation. We develop two novel classifier aggregation methods which utilize local classification confidence and we compare them to two commonly used methods for classifier aggregation. The results on four artificial and five real-world benchmark datasets show that by incorporating local classification confidence into classifier aggregation methods, significant improvement in classification quality can be obtained." . "ICAART 2009" . . "Classifier aggregation is a method for improving quality of classification. Instead of using just one classifier, a team of classifiers is created, and the outputs of the individual classifiers are aggregated into the final prediction. In this paper, we study the potential of using measures of local classification confidence in classifier aggregation methods. We introduce four measures of local classification confidence and study their suitability for classifier aggregation. We develop two novel classifier aggregation methods which utilize local classification confidence and we compare them to two commonly used methods for classifier aggregation. The results on four artificial and five real-world benchmark datasets show that by incorporating local classification confidence into classifier aggregation methods, significant improvement in classification quality can be obtained."@en . . . . . "Classifier Aggregation Using Local Classification Confidence"@en . . . "2009-01-19+01:00"^^ . "Spojov\u00E1n\u00ED klasifik\u00E1tor\u016F pomoc\u00ED lok\u00E1ln\u00ED konfidence klasifikace"@cs . . "RIV/67985807:_____/09:00320925!RIV09-AV0-67985807" . "Porto" . . "Spojov\u00E1n\u00ED klasifik\u00E1tor\u016F pomoc\u00ED lok\u00E1ln\u00ED konfidence klasifikace"@cs . "Classifier Aggregation Using Local Classification Confidence" . "2"^^ . "Classifier Aggregation Using Local Classification Confidence" . . . "2"^^ . "\u0160tefka, David" . "000267058000026" . "Classifier Aggregation Using Local Classification Confidence"@en . "[978B58E3A4CC]" .