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We present a boosting method for classification problems with optimal AUC value as a performance measure. The proposed technique first minimizes the empirical pairwise classification error. Once the pairwise classification error is reduced to a coordinatewise local minimum, then it switches to maximize the average pairwise margin of a small set of bottom sample pairs. Experimental results on real-world...
The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of hyperspectral images has been proposed. The central...
Web contents are going overwhelming today. The numerous online documents, webpages, e-books, etc. are much useful but obtaining them is also time-consuming. Text categorization is one of the solutions to the issue. For all text categorization method, Support Vector Machines (SVM) is one of the most acceptable one. However, to perform more efficiently on webpages, it is necessary to add improvements...
In this paper we present a new method for object categorization. Firstly an image representation is obtained by the proposed hierarchical learning method consisting of alternating between local coding and maximum pooling operations, where the local coding operation induces discrimination while the image descriptor and maximum pooling operation induces invariance in hierarchical architecture. Then...
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