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In this paper, the brief survey of data mining classification by using the machine learning techniques is presented. The machine learning techniques like decision tree and support vector machine play the important role in all the applications of artificial intelligence. Decision tree works efficiently with discrete data and SVM is capable of building the nonlinear boundaries among the classes. Both...
Support vector machine (SVM) is one of the best machine learning models that offers high accuracy both for recognition and for regression. One drawback of using SVM is that the system implementation cost is usually proportional to the number of training data and the dimension of the feature space. Therefore, it is difficult to use SVM in mobile devices such as IC cards and smart phones. In our study,...
The algorithm based on multi-feature and SVM is proposed. The paper firstly uses wavelet de-noising for gait images. The text offers to use width descriptors as gait features and combines lower angle features. The kernel-based Fisher criterion and support vector machine is combined to classification and identification. The gait characteristic is extracted by KFDA, which can obtain the best projection...
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