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  • This paper describes the use of the macro language STATISTICA Visual Basic to construct receiver operating characteristics curves (ROC) for both the parametric and nonparametric classification algorithms implemented in the statistical and data mining software STATISTICA. ROC curves are widely used as a tool to evaluate classification models, but STATISTICA has an option of ROC curves only for neural networks. The macro presented here allows constructing the ROC curve for any classification model that provides estimates of the posterior probabilities. It displays the ROC curves in a single graph, therefore the classifiers comparison is facilitated. The nonparametric estimates of the area under the curve (AUC) and its standard error are provided by the macro using Mann-Whitney statistic. These estimates are used to construct the confidence limits for the area under the curve and can be used to test the hypothesis for the difference of AUC between two ROC curves provided that the ROC curves were construc
  • This paper describes the use of the macro language STATISTICA Visual Basic to construct receiver operating characteristics curves (ROC) for both the parametric and nonparametric classification algorithms implemented in the statistical and data mining software STATISTICA. ROC curves are widely used as a tool to evaluate classification models, but STATISTICA has an option of ROC curves only for neural networks. The macro presented here allows constructing the ROC curve for any classification model that provides estimates of the posterior probabilities. It displays the ROC curves in a single graph, therefore the classifiers comparison is facilitated. The nonparametric estimates of the area under the curve (AUC) and its standard error are provided by the macro using Mann-Whitney statistic. These estimates are used to construct the confidence limits for the area under the curve and can be used to test the hypothesis for the difference of AUC between two ROC curves provided that the ROC curves were construc (en)
  • Příspěvek popisuje využití makrojazyka STATISTICA Visual Basic k sestavení ROC křivek pro parametrické i neparametrické klasifikační algoritmy implementované ve statistickém a data miningovém systému STATISTICA. ROC křivky jsou běžně používány k hodnocení klasifikačních modelů, avšak STATISTICA sestavuje ROC křivky pouze pro neuronové sítě. Prezentované makro umožňuje sestavení ROC křivky pro jakýkoli klasifikační model, který poskytuje odhady aposteriorních pravděpodobností, a který byl uložen v PMML formátu (Predictive Model Markup Language). ROC křivky jsou zobrazovány v jednom grafu tak, aby bylo usnadněno vzájemné porovnání několika klasifikačních modelů. Jedním z nejčastěji používaných souhrnných indexů kvality modelu je plocha pod křivkou (AUC), která je tímto makrem počítána. Odhad plochy pod křivkou a její směrodatné chyby je prováděn neparametricky pomocí Mann-Whitney statistiky. Odhady směrodatných chyb jsou používány k sestavení intervalů spolehlivostí pro dané plochy pod křivkou. Lze je t (cs)
Title
  • ROC Curves for the Classification Algorithms in STATISTICA Data Miner
  • ROC křivky pro klasifikační algorimy ve Statistica Data Miner (cs)
  • ROC Curves for the Classification Algorithms in STATISTICA Data Miner (en)
skos:prefLabel
  • ROC Curves for the Classification Algorithms in STATISTICA Data Miner
  • ROC křivky pro klasifikační algorimy ve Statistica Data Miner (cs)
  • ROC Curves for the Classification Algorithms in STATISTICA Data Miner (en)
skos:notation
  • RIV/62690094:18450/07:00001869!RIV07-GA0-18450___
http://linked.open.../vavai/riv/strany
  • 363-368
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA402/04/1308)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 448095
http://linked.open...ai/riv/idVysledku
  • RIV/62690094:18450/07:00001869
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • classification; classifiers evaluation; ROC curves; data mining (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D7FAF3350A49]
http://linked.open...i/riv/mistoVydani
  • Bratislava
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 6th International Conference Aplimat 2007
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Jakoubek, Bohumil
number of pages
http://purl.org/ne...btex#hasPublisher
  • Slovenská technická univerzita v Bratislave
https://schema.org/isbn
  • 978-80-969562-4-1
http://localhost/t...ganizacniJednotka
  • 18450
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