In machine learning, ensemble classifiers have been introduced for more accurate pattern classification than single classifiers. We propose a new ensemble learning method that emp...
This paper points out some drawbacks and proposes some modifications to the conventional layer-by-layer BP algorithm. In particular, we present a new perspective to the learning ra...
Xu-Qin Li, Fei Han, Tat-Ming Lok, Michael R. Lyu, ...
Self-training is a semi-supervised learning algorithm in which a learner keeps on labeling unlabeled examples and retraining itself on an enlarged labeled training set. Since the s...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Abstract- Interactive combat games are useful as testbeds for learning systems employing evolutionary computation. Of particular value are games that can be modified to accommodate...