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Temporal Probability Calibration
In many applications, accurate class probability estimates are required, but many types of models produce poor quality probability estimates despite achieving acceptable classification accuracy.
Ensembles of Nested Dichotomies with Multiple Subset Evaluation
A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems.
On the Calibration of Nested Dichotomies for Large Multiclass Tasks
Nested dichotomies are used as a method of transforming a multiclass classification problem into a series of binary problems.
Probability Calibration Trees
Obtaining accurate and well calibrated probability estimates from classifiers is useful in many applications, for example, when minimising the expected cost of classifications.
Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection
A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems.
