The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Multiple observation improves the performance of 3D object classification. However, since the distribution of feature vectors obtained from multiple view points have strong nonlin...
We propose a novel technique for automatically generating the SCOP classification of a protein structure with high accuracy. High accuracy is achieved by combining the decisions o...
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
In this work we consider the problem of binary classification where the classifier may abstain instead of classifying each observation, leaving the critical items for human evaluat...