Optimization Based Data Mining: Theory and Applications | |
by: Yong Shi, Y. Tian, G. Kou, Y. Peng, J. Li |
Springer-Verlag London Limited 2011
Contents
Part I Support Vector Machines: Theory and Algorithms
1 Support Vector Machines for Classification Problems . . . . . . . . . 3
2 LOO Bounds for Support Vector Machines . . . . . . . . . . . . . . 15
3 Support Vector Machines for Multi-class Classification Problems . . 47
4 Unsupervised and Semi-supervised Support Vector Machines . . . . 61
5 Robust Support Vector Machines . . . . . . . . . . . . . . . . . . . . 81
6 Feature Selection via lp-Norm Support Vector Machines . . . . . . . 107
Part II Multiple Criteria Programming: Theory and Algorithms
7 Multiple Criteria Linear Programming . . . . . . . . . . . . . . . . . 119
8 MCLP Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
9 Multiple Criteria Quadratic Programming . . . . . . . . . . . . . . . 157
10 Non-additive MCLP . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
11 MC2LP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
Part III Applications in Various Fields
12 Firm Financial Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 195
13 Personal Credit Management . . . . . . . . . . . . . . . . . . . . . . 203
14 Health Insurance Fraud Detection . . . . . . . . . . . . . . . . . . . 233
15 Network Intrusion Detection . . . . . . . . . . . . . . . . . . . . . . 237
16 Internet Service Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 243
17 HIV-1 Informatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
18 Anti-gen and Anti-body Informatics . . . . . . . . . . . . . . . . . . 259
19 Geochemical Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . 269
20 Intelligent Knowledge Management . . . . . . . . . . . . . . . . . . 277