Data structures and algorithm analysis in C (2nd ed.)
Data structures and algorithm analysis in C (2nd ed.)
A Simple Approach to Ordinal Classification
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Prediction of Ordinal Classes Using Regression Trees
ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
The Journal of Machine Learning Research
Probability Estimates for Multi-class Classification by Pairwise Coupling
The Journal of Machine Learning Research
New approaches to support vector ordinal regression
ICML '05 Proceedings of the 22nd international conference on Machine learning
A support vector method for multivariate performance measures
ICML '05 Proceedings of the 22nd international conference on Machine learning
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Bounds on Error Expectation for Support Vector Machines
Neural Computation
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Learning to Classify Ordinal Data: The Data Replication Method
The Journal of Machine Learning Research
ROC analysis in ordinal regression learning
Pattern Recognition Letters
Trust Region Newton Method for Logistic Regression
The Journal of Machine Learning Research
Label ranking by learning pairwise preferences
Artificial Intelligence
Artificial Intelligence in Medicine
Binary Decomposition Methods for Multipartite Ranking
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
An Improved DAG-SVM for Multi-class Classification
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 01
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
ECML'06 Proceedings of the 17th European conference on Machine Learning
Text classification for DAG-Structured categories
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Preferences in AI: An overview
Artificial Intelligence
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Multipartite ranking is a special kind of ranking for problems in which classes exhibit an order. Many applications require its use, for instance, granting loans in a bank, reviewing papers in a conference or just grading exercises in an education environment. Several methods have been proposed for this purpose. The simplest ones resort to regression schemes with a pre- and post-process of the classes, what makes them barely useful. Other alternatives make use of class order information or they perform a pairwise classification together with an aggregation function. In this paper we present and discuss two methods based on building a Decision Directed Acyclic Graph (DDAG). Their performance is evaluated over a set of ordinal benchmark data sets according to the C-Index measure. Both yield competitive results with regard to state-of-the-art methods, specially the one based on a probabilistic approach, called PR-DDAG.