By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
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
When a lack of data inhibits decision making, large scale what-if queries can be conducted over the uncertain parameter ranges. Such what-if queries can generate an overwhelming a...
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...