0000000000848516

AUTHOR

Jinkyoo Park

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Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)

2017

International audience; This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the pred…

Computer sciencecomputer.internet_protocol02 engineering and technologycomputer.software_genreIndustrial and Manufacturing EngineeringArticleSet (abstract data type)[SPI]Engineering Sciences [physics]Kriging020204 information systems0202 electrical engineering electronic engineering information engineeringUncertainty quantificationRepresentation (mathematics)predictive model markup language (PMML)Probabilistic logicdata miningPredictive analyticsXMLComputer Science Applicationspredictive analyticsControl and Systems EngineeringPredictive Model Markup Languagestandards020201 artificial intelligence & image processingData miningcomputerXMLGaussian process regression
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