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Using a large national health database, we propose an enhanced SVM-based model called Hierarchical Clustering Support Vector Machine (HCSVM) that utilizes multiple levels of clusters to classify patients diagnosed with type-2 diabetes. Multiple HCSVMs are trained for clusters at different levels of the hierarchy. Some clusters at certain levels of the hierarchy capture more separable sample spaces...
In real-world applications, labeled data are often inadequate while unlabeled data are available in large quantities. Many semi-supervised learning (SSL) algorithms are proposed to take advantage of unlabeled data. In this paper we propose a novel wrapper method for semi-supervised learning called graph-based selection wrapper (GSW), which aims to improve an existing classifier in a semi-supervised...
In this paper, we present a face recognition method based on the combination of the LoG-Gabor wavelets (GW) and the phase congruency (PC) method. The phase congruency feature images were obtained by applying phase congruency model to these multi-view face images with log-Gabor wavelets filters over 5 scales and 8 orientations, and then the mean and standard deviation of the image output are computed...
Human face recognition plays an important role in applications such as video surveillance, human computer interface, and face image database management. This paper presents an improved face recognition method for multi-pose face recognition in color images, which addresses the problems of illumination and pose variation. At first, color multi-pose faces image features were extracted based on Gabor...
Local protein structure prediction is a central task in bioinformatics research. Local protein structure prediction can be transformed into the multiclass problem for huge datasets. In previous study, multiclass clustering support vector machines (CSVMs) was proposed for local protein structure prediction. The greedy algorithm is utilized to select the next closest class if CSVM modeled for the assigned...
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