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Supervised Learning (SL) is a machine learning research area which aims at developing techniques able to take advantage from labeled training samples to make decisions over unseen examples. Recently, a lot of tools have been presented in order to perform machine learning in a more straightforward and transparent manner. However, one problem that is increasingly present in most of the SL problems being...
While advances in sensor and signal processing techniques have provided effective tools for quantitative research on traditional Chinese pulse diagnosis (TCPD), the automatic classification of pulse waveforms is remained a difficult problem. To address this issue, this paper proposed a novel edit distance with real penalty (ERP)-based k-nearest neighbors (KNN) classifier by referring to recent progresses...
Scene images typically include diverse and distinctive properties. It is reasonable to consider different features in establishing a scene category recognition system with a promising performance. We propose an adaptive model to represent various features in a unified domain, i.e., a set of kernels, and transform the discriminant information contained in each kernel into a set of weak learners, called...
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