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We consider the problem of SVM batch active learning, which involves distinguishing samples chosen and maximum approximate the real normal vector w in feature space. Although several studies are devoted to batch mode active learning, they suffer either from the uncertain parameter set or from the solutions of local optimization. We introduce a new algorithm for performing batch active learning by...
Multiple kernel learning (MKL) approach for selecting and combining different representations of a data is presented. Selection of features from a representation of data using the MKL approach is also addressed. A base kernel function is used for each representation as well as for each feature from a representation. A new kernel is obtained as a linear combination of base kernels, weighted according...
Ant colony optimization (ACO) is a kind of bionic swarm intelligence algorithm belongs to artificial intelligence (AI) field and has been successfully applied in resolving complex optimization problems. Support vector machine (SVM) is a new machine learning method with greater generalization performance, and has shown its superiority in classification and regression problems. By combining the advantages...
With the increase of the training set??s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel pre-extracting method for SVM classification is proposed in this paper. In SVM classification, only support vectors (SVs) have significant influence on the optimization result. We adopt a non-parametric k-NN rule called relative neighborhood graph...
Spontaneous Combustion in Coal Seam (SCCS) is seriously threatening coal mine safety. A novel approach to predict SCCS by using Support Vector Machine (SVM) is present. The SVM is based on statistical learing theory with a simple structure and good generation properties. The basic SVM principle was firstly reviewed. Then, the kernel function was choiced, and the model parameters were optimized with...
Wireless multimedia sensor network (WMSN) has powerful multimedia signal acquisition and processing abilities. This paper proposes a collaborative hybrid classifier learning algorithm to achieve online support vector machine (SVM) learning for robust target classification in WMSN. The proposed algorithm is carried out in a hybrid computing paradigm, which combines the advantages of progressive computing...
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