In statistics, ordinal regression (also called "ordinal classification") is a type of regression analysis used for predicting an ordinal variable, i… (More)

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Highly Cited

2015

Highly Cited

2015

- Bin Gu, Victor S. Sheng, KengYeow Tay, Walter Romano, Shuo Li
- IEEE Transactions on Neural Networks and Learning…
- 2015

Support vector ordinal regression (SVOR) is a popular method to tackle ordinal regression problems. However, until now there were… (More)

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2010

2010

- Bing-Yu Sun, Jiuyong Li, Desheng Dash Wu, Xiaoming Zhang, Wenbo Li
- IEEE Transactions on Knowledge and Data…
- 2010

Ordinal regression has wide applications in many domains where the human evaluation plays a major role. Most current ordinal… (More)

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Highly Cited

2007

Highly Cited

2007

- Wei Chu, S. Sathiya Keerthi
- Neural Computation
- 2007

In this letter, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define… (More)

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2007

2007

- Rashmin Babaria, J. Saketha Nath, S. Krishnan, K. R. Sivaramakrishnan, Chiranjib Bhattacharyya, M. Narasimha Murty
- ICML
- 2007

In this paper we propose a novel, scalable, clustering based Ordinal Regression formulation, which is an instance of a Second… (More)

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Highly Cited

2006

Highly Cited

2006

- Ling Li, Hsuan-Tien Lin
- NIPS
- 2006

We present a reduction framework from ordinal regression to binary classification based on extended examples. The framework… (More)

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2006

2006

- Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
- ICML
- 2006

Ordinal regression has become an effective way of learning user preferences, but most research focuses on single regression… (More)

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Highly Cited

2005

Highly Cited

2005

- Wei Chu, Zoubin Ghahramani
- Journal of Machine Learning Research
- 2005

We present a probabilistic kernel approach to ordinal regression based on Gaussian processes. A threshold model that generalizes… (More)

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Highly Cited

2005

Highly Cited

2005

- Wei Chu, S. Sathiya Keerthi
- ICML
- 2005

In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define… (More)

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Highly Cited

1999

Highly Cited

1999

We investigate the problem of predicting variables of ordinal scale. This taks is referred to as ordinal regression and is… (More)

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Highly Cited

1999

Highly Cited

1999

In contrast to the standard machine learning tasks of classi cation and metric regression we investigate the problem of… (More)

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