Weighted voting is the commonly used strategy for combining predictions in pairwise classification. Even though it shows excellent performance in practice, it is often criticized ...
Neuroimaging datasets often have a very large number of voxels and a very small number of training cases, which means that overfitting of models for this data can become a very se...
Tanya Schmah, Geoffrey E. Hinton, Richard S. Zemel...
Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This pa...
— The build up of water ice on aircraft flight surfaces poses a significant safety risk. As a result, much effort has gone into studying this problem in order to understand how i...
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...