In this paper, we show that a continuous spectrum of randomisation exists, in which most existing tree randomisations are only operating around the two ends of the spectrum. That ...
Fei Tony Liu, Kai Ming Ting, Yang Yu, Zhi-Hua Zhou
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Abstract. We study various ensemble methods for hybrid neural networks. The hybrid networks are composed of radial and projection units and are trained using a deterministic algori...
Abstract. One of the more challenging problems faced by the data mining community is that of imbalanced datasets. In imbalanced datasets one class (sometimes severely) outnumbers t...
The advent of real-time fMRI pattern classification opens many avenues for interactive self-regulation where the brain's response is better modelled by multivariate, rather t...
Catrin Oliver Plumpton, Ludmila I. Kuncheva, David...