Random forest induction is a bagging method that randomly samples the feature set at each node in a decision tree. In propositional learning, the method has been shown to work well...
Celine Vens, Anneleen Van Assche, Hendrik Blockeel...
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Abstract Features computed as statistics (e.g. histograms) of local filter responses have been reported as the most powerful descriptors for texture classification and segmentation...
—In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be extracted from the electroencephalogram (EEG) using the Common Spatial Pattern (CSP) algor...
Kai Keng Ang, Zhang Yang Chin, Haihong Zhang, Cunt...