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Machine Learning - Modeling Data Locally and Globally
von: Kaizhu Huang, Haiqin Yang, Irwin King, Michael Lyu
Springer-Verlag, 2008
ISBN: 9783540794523, 179 Seiten
Format: PDF, OL
Preis: 139,05 EUR
Preface
6
Contents
7
1 Introduction
11
1.1 Learning and Global Modeling
11
1.2 Learning and Local Modeling
13
1.3 Hybrid Learning
15
1.4 Major Contributions
15
1.5 Scope
18
References
19
2 Global Learning vs. Local Learning
23
2.1 Problem De.nition
25
2.2 Global Learning
26
2.4 Hybrid Learning
33
2.5 Maxi-Min Margin Machine
34
References
35
3 A General Global Learning Model: MEMPM
39
3.1 Marshall and Olkin Theory
40
3.2 Minimum Error Minimax Probability Decision Hyperplane
41
3.3 Robust Version
55
3.4 Kernelization
56
3.5 Experiments
60
3.6 How Tight Is the Bound?
66
3.7 On the Concavity of MEMPM
70
3.8 Limitations and Future Work
75
3.9 Summary
76
References
77
4 Learning Locally and Globally: Maxi-Min Margin Machine
79
4.1 Maxi-Min Margin Machine
81
4.2 Bound on the Error Rate
92
4.3 Reduction
94
4.4 Kernelization
95
4.5 Experiments
98
4.6 Discussions and Future Work
103
4.7 Summary
103
References
104
5 Extension I: BMPM for Imbalanced Learning
107
5.1 Introduction to Imbalanced Learning
108
5.2 Biased Minimax Probability Machine
108
5.3 Learning from Imbalanced Data by Using BMPM
110
5.4 Experimental Results
112
5.5 When the Cost for Each Class Is Known
124
5.6 Summary
125
References
125
6 Extension II: A Regression Model from M4
129
6.1 A Local Support Vector Regression Model
131
6.2 Connection with Support Vector Regression
132
6.3 Link with Maxi-Min Margin Machine
134
6.4 Optimization Method
134
6.5 Kernelization
135
6.6 Additional Interpretation on wTSiw
137
6.7 Experiments
138
6.8 Summary
141
References
141
7 Extension III: Variational Margin Settings within Local Data in Support Vector Regression
143
7.1 Support Vector Regression
144
7.2 Problem in Margin Settings
146
7.3 General -insensitive Loss Function
146
7.4 Non-.xed Margin Cases
149
7.5 Experiments
151
7.6 Discussions
165
References
168
8 Conclusion and Future Work
171
8.1 Review of the Journey
171
8.2 Future Work
173
References
174
Index
177
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