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
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