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Nowadays, as the development of mobile communication, it is very important to serve users. Because of the subjectivity of user experience, the data of user experience has deviation. In the paper, a cooperative modeling method based on the improved Support Vector Machine is proposed, which can evaluate the quality of experience by using measurement report. The results of the experiments show that our...
SVM is not as favored for large-scale data training as for Network Intrusion Detection because the training complexity of SVM is highly dependent on the size of training sample set. And the network information includes a large number of noise data that impact on constructing the boundary (separating hyperplane) of SVM. Some redundant sample points and noisy points are firstly removed in this paper...
A large number of noise data always exits when obtaining information through Internet, which deteriorates intrusion detection performance. In order to avoid the affection of noise data, data preprocessing needs to be done before the construction of hyperplane in Support Vector Machine (SVM). By importing fuzzy theory into SVM, a new method is proposed for cooperative network intrusion detection. Due...
It is important that the training time of the Support Vector Machine (SVM) is shortened and storage space requirement is reduced for high-speed and large-scale network. An intrusion detection method based on parallel SVM is proposed and a detection model system is constructed in this paper. First, original training dataset gained from network is divided into three subsets according to the network...
One of the main difficulties in machine learning is how to solve large-scale problems effectively, and the labeled data are limited and fairly expensive to obtain. In this paper a new semi-supervised SVM algorithm is proposed. It applies tri-training to improve SVM. The semi-supervised SVM makes use of the large number of unlabeled data to modify the classifiers iteratively. Although tri-training...
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