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Found 5 papers, 1 papers with code
Solving for multi-class: a survey and synthesis
The best solution for the most improved dataset exploited a property of the data to produce an uncertainty coefficient 36\% higher (0. 016 absolute gain) than one-vs.-one.
Solving for multi-class using orthogonal coding matrices
When the methods are paired with SVM, the losses are less significant, peaking at 1. 5%, relative, 0. 011 absolute in uncertainty coefficient and 6. 5% in Brier scores.
Accelerating Kernel Classifiers Through Borders Mapping
Because the component linear classifiers are built up individually from an existing classifier, rather than through a simultaneous optimization procedure, the classifier is also fast to train.
Multi-borders classification
The number of possible methods of generalizing binary classification to multi-class classification increases exponentially with the number of class labels.
Efficient statistical classification of satellite measurements
Because of the high resolution of modern satellite instruments and because of the requirement for real-time processing, any algorithm has to be fast to be useful.
