Results 51 to 60 of about 5,941,658 (334)
Selection of Ordinally Scaled Independent Variables [PDF]
, 2009 Ordinal categorial variables are a common case in regression modeling. Although the case of ordinal response variables has been well investigated, less work has been done concerning ordinal predictors.
Gertheiss, Jan +3 more
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Geographically Weighted Probit Ordinal Regression Model Estimation [PDF]
E3S Web of ConferencesGeographically Weighted Probit Ordinal Regression (GWPOR) is a combined method between Geographically Weighted Regression and Probit Ordinal Regression. This study estimates the percentage of poor people using the GWPOR method.
Kurniawan Muh. Idham +2 more
doaj +1 more source
Weighted k-Nearest-Neighbor Techniques and Ordinal Classification [PDF]
, 2004 In the field of statistical discrimination k-nearest neighbor classification is a well-known, easy and successful method. In this paper we present an extended version of this technique, where the distances of the nearest neighbors can be taken into ...
Schliep, Klaus +3 more
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Generating Correlated Ordinal Random Values [PDF]
, 2011 Ordinal variables appear in many field of statistical research. Since working with simulated data is an accepted technique to improve models or test results there is a need for providing correlated ordinal random values with certain properties like ...
Leisch, Friedrich +2 more
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Simultaneous optimization of quantitative and ordinal responses using Taguchi method [PDF]
International Journal of Research in Industrial Engineering, 2018 In the real world, the overall quality of a product is often represented partly by the measured values of some quantitative variables and partly by the observed values of some ordinal variables.
S. Pal, S. Gauri
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Evaluation Measures for Ordinal Regression
2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009 Ordinal regression (OR -- also known as ordinal classification) has received increasing attention in recent times, due to its importance in IR applications such as learning to rank and product review rating. However, research has not paid attention to the fact that typical applications of OR often involve datasets that are highly imbalanced.
Baccianella S, Esuli A, Sebastiani F
openaire +4 more sources
Ordinal regression model for pea seed mass
Die Bodenkultur, 2017 The development of seeds at various positions in the pod is asynchronous. Thus, the differences of seed dry mass production because of environmental conditions may depend on the cultivar type, type of inoculants and interrelations between seeds per pod ...
Klimek-Kopyra Agnieszka +5 more
doaj +1 more source
Revista de Saúde Pública, 2009 Os modelos de regressão logística ordinal vêm sendo aplicados com sucesso na análise de estudos epidemiológicos. Entretanto, a verificação da adequação de cada modelo tem recebido atenção limitada.
Mery Natali Silva Abreu +2 more
doaj +1 more source
, 2016 Regression Modeling Strategies is an advanced text, aimed at graduate students and re-searchers with a solid, comprehensive background in regression modeling. Readers should have a good working knowledge of regression analysis as well as R as all code is
James E. Helmreich
semanticscholar +1 more source
Minimum enclosing spheres formulations for support vector ordinal regression [PDF]
, 2006 We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples.
S.K. Shevade +3 more
core +1 more source