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Recently ensemble classification has attracted serious attention of machine learning community as a solution for improving classification accuracy. The effect of the strategies for generating the members, combining the predictions and the size of the ensemble on the accuracy of the ensemble are of utmost interest to the researchers. In this paper, we propose and empirically evaluate a novel method...
Stream ciphers are widely used for information security. The keystream produced by a cipher must be unpredictable. Attacks on stream ciphers typically exploit some underlying patterns existing in the keystream. The objective of this paper is to develop such an attack with the help of machine learning algorithms. The Linear Feedback Shift Register (LFSR) has been solved for several test cases using...
Support vector machine is a new machine learning technique developed on the basis of statistical learning theory, which has become the hotspot of machine learning because of its excellent learning performance. Based on analyzing the theory of support vector machine for regression (SVR), a SVR model is established for predicting the output in fully mechanized mining face, and then realizes the model...
This paper deals with the study of a water quality prediction model through application of LS-SVM in Liuxi River in Guangzhou. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value, least squares support vector machine (LS-SVM) combined with particle swarm optimization (PSO) is used to time series prediction. The LS-SVM can overcome...
With the rapid development of real estate, the risk of investment is also increasing rapidly. So the risk of predicting and controlling the real estate investment has become the key to the success or failure of the project. In this paper, a support vector machine (SVM) modeling approach for real estate investment risk prediction is proposed at first, which is made use of its merits of structural risk...
Telecom churn prediction is one of the key factors which closely related to the development of telecommunications business. To solve the data imbalance problem exiting in this field, traditional researches always redistribute samples according to misclassification cost. But exiting researches in this area neither gave out the quantitative description of the misclassification cost nor set up a unified...
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