Results 51 to 60 of about 96,053 (159)
Effect Structures in Ordinal Regression: The Adjacent Categories Approach
StatsThe potential of the adjacent categories approach for capturing the influence of explanatory variables on ordinal responses is investigated. Several models with increasing complexity in their linear predictors are considered, and their relationships are ...
Gerhard Tutz
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Forecasting of wheat (Triticum aestivum) yield using ordinal logistic regression
The Indian Journal of Agricultural Sciences, 2014 In this study, uses of ordinal logistic model based on weather data has been attempted for forecasting wheat (Triticum aestivum L.) yield in Kanpur district of Uttar Pradesh.
VANDITA KUMARI, AMRENDER KUMAR
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Regression Models for Ordinal Data
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1980 Summary A general class of regression models for ordinal data is developed and discussed. These models utilize the ordinal nature of the data by describing various modes of stochastic ordering and this eliminates the need for assigning scores or otherwise assuming cardinality instead of ordinality.
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Unimodal Distributions for Ordinal Regression
IEEE Transactions on Artificial Intelligence17 ...
Jaime S. Cardoso 0001 +2 more
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, 2014 Any multiple Criteria Decision Aiding (MCDA) method needs some preference parameters. The Decision Maker (DM) could be asked to provide directly all these parameters; however, because it needs a great cognitive effort, the indirect preference information is more used in practice. Starting from the indirect preference information, usually there could be
Corrente S +3 more
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Calibration of Ordinal Regression Networks
CoRRRecent studies have shown that deep neural networks are not well-calibrated and often produce over-confident predictions. The miscalibration issue primarily stems from using cross-entropy in classifications, which aims to align predicted softmax probabilities with one-hot labels.
Daehwan Kim, Haejun Chung, Ikbeom Jang
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ENSEMBLE BAGGING WITH ORDINAL LOGISTIC REGRESSION TO CLASSIFY TODDLER NUTRITIONAL STATUS
BarekengOne problem in classifying stunting data is that the data used does not have a balanced proportion. This study aims to apply the logistic regression classification method with ordinal scale response variables to overcome class imbalance through the ...
Luthfia Hanun Yuli Arini +3 more
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OSNR Monitoring Using Support Vector Ordinal Regression for Digital Coherent Receivers
IEEE Photonics Journal, 2019 An OSNR monitoring method assisted by support vector ordinal regression (SVOR) is proposed for digital coherent receivers. According to Godard's error of equalized signals obtained after polarization demultiplexing, the optical signal-to-noise ...
Ming Hao +6 more
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Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer
International Journal of Computer Science in Sport, 2017 Ordinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred ...
Hvattum L. M.
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Ordinal logistic regression [PDF]
American Journal of Orthodontics and Dentofacial Orthopedics, 2018 Koletsi D, Pandis N
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