Machine Learning can be divided into two schools of thought: generative model learning and discriminative model learning. While the MCS community has been focused mainly on the lat...
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
The assessment of the reliability of clusters discovered in bio-molecular data is a central issue in several bioinformatics problems. Several methods based on the concept of stabil...
We experimentally evaluate bagging and six other randomization-based approaches to creating an ensemble of decision-tree classifiers. Bagging uses randomization to create multipl...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
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