This paper presents a method for obtaining class membership probability estimates for multiclass classification problems by coupling the probability estimates produced by binary c...
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...
A novel method of learning complex fuzzy decision regions in the n-dimensional feature space is proposed. Through the fuzzy decision regions, a given pattern's class membershi...