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Feature selection for ensembles can often improve generalization accuracy of classifiers. In this paper we present a strategy on the feature selection for ensembles based on a hierarchical Non-dominated Sorting in Genetic Algorithms (NSGA-II) proposed by Deb. The first level of our strategy performs feature selection in order to generate a set of good classifiers, the second one deletes redundant...
Automatic recognition of skin symptom plays an importance role in the skin diagnosis and treatment. Feature selection is to increase the classification performance of skin symptom. In this paper, the effects of feature selection on the classification of 4-class skin symptoms (chloasma, blackhead, freckled and comedone) are analyzed. Support vector machine (SVM) is employed to construct classifier,...
With the development and widely used of Internet and information technology, the Web has become one of the most important means to obtain information for people. According to the Web document classification and the theory of artificial neural network, a Web classification mining method based on classify support vector machine (SVM) is presented in this paper. The SVM network structure that used for...
Standard machine learning techniques like support vector machines (SVM) and related large margin methods have been successfully applied for text classification. Unfortunately, the high dimensionality of input feature vectors impacts on the classification speed. The kernel parameters setting for SVM in a training process impacts on the classification accuracy. Feature selection is another factor that...
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