Chapter I Introduction of SVM 1.1 SVM 1.2 Binary Classification Chapter II Sample Reduction and Attribute Selection in SVM 2.1 The Design and Performance of Intrusion Detection System Classifier Based on the Time Series Windows 2.2 Application of PSVM and Data Processing for Intrusion Detection 2.3 Less is More:Data Processing with SVM for Intrusion Detection Chapter III Parameter Selection of SVM 3.1 Principle of BSA 3.2 BSA-SVM Algorithm Design 3.3 BSA-SVM Algorithm Principle 3.4 BSA-SVM Algorithm Simulation Experiment 3.5 Conclusion Chapter IV Fusion Classification Based on SVM 4.1 Intrusion Detection Using Ensemble of SVM Classifiers 4.2 An Integrated Decision System for Intrusion Detection 4.3 Intrusion Detection in Ad-hoc Networks Chapter V Intelligence Classification Based on SVM 5.1 Introduction 5.2 An Overview of Active Learning 5.3 Methodology 5.4 Experiments 5.5 Conclusion Chapter VI SVM Based on Privileged Information 6.1 Support Vector Classification Using Partial Privileged Information 6.2 A New Learning Paradigm:Learning Using Partial Privileged Information References
鄂公網(wǎng)安備 42010302001612號(hào) 