Results 31 to 40 of about 96,420 (258)
Twitter Sentiment Analysis Based on Ordinal Regression
IEEE Access, 2019 In recent years, research on Twitter sentiment analysis, which analyzes Twitter data (tweets) to extract user sentiments about a topic, has grown rapidly. Many researchers prefer the use of machine learning algorithms for such analysis.
Shihab Elbagir Saad, Jing Yang
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Feature selection for ordinal regression [PDF]
Proceedings of the 2010 ACM Symposium on Applied Computing, 2010 Ordinal classification (also known as ordinal regression) is a supervised learning task that consists of automatically determining the implied rating of a data item on a fixed, discrete rating scale. This problem is receiving increasing attention from the sentiment analysis and opinion mining community, due to the importance of automatically rating ...
Baccianella S, Esuli A, Sebastiani F
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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
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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
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Pairwise Fairness for Ordinal Regression
CoRR, 2021 We initiate the study of fairness for ordinal regression. We adapt two fairness notions previously considered in fair ranking and propose a strategy for training a predictor that is approximately fair according to either notion. Our predictor has the form of a threshold model, composed of a scoring function and a set of thresholds, and our strategy is ...
Kleindessner, M. +4 more
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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
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Regression with Ordered Predictors via Ordinal Smoothing Splines
Frontiers in Applied Mathematics and Statistics, 2017 Many applied studies collect one or more ordered categorical predictors, which do not fit neatly within classic regression frameworks. In most cases, ordinal predictors are treated as either nominal (unordered) variables or metric (continuous) variables ...
Nathaniel E. Helwig, Nathaniel E. Helwig
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Dwell Time Estimation of Import Containers as an Ordinal Regression Problem
Applied Sciences, 2021 The optimal stacking of import containers in a terminal reduces the reshuffles during the unloading operations. Knowing the departure date of each container is critical for optimal stacking.
Laidy De Armas Jacomino +5 more
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Predictive Factors for Pelvic Organ Prolapse (POP) in Iranian Women’s: An Ordinal Logistic Approch [PDF]
Journal of Clinical and Diagnostic Research, 2014 Introduction: To investigate the predictors factors of Pelvic Organ Prolapse (POP) in Iranian women by using ordinal logistic regression. Materials and Methods: The role of risk factors of POP was evaluated among 365 patients attending in two public ...
Ashraf Direkvand-Moghadam +2 more
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