Title Statements
- Full title :Data-variant kernel analysis / Yuichi Motai, Sensory Intelligence Laboratory, Department of Electrical and Computer Engineering, Virginia Commonwealth University Richmond, VA.
Summary
"This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications"--
Read More ↓Edition Statements
- Publication Date:2015.
Publication Statements
- Publisher(s):Wiley
- Place of Publication:Hoboken, New Jersey
- Language:eng
- Publication Date:2015.
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9781119019343, 1119019346, 9781119019336, 1119019338, 9781119019350, 1119019354, 111901932X, 9781119019329
- oclc:ocn904047560
- LC Classification:QA353.K47
- Dewey Decimal:515/.9
Table of Contents
Cover; Title Page; Copyright; Contents; List of Figures; List of Tables; Preface; Acknowledgments; Chapter 1 Survey; 1.1 Introduction of Kernel Analysis; 1.2 Kernel Offline Learning; 1.2.1 Choose the Appropriate Kernels; 1.2.2 Adopt KA into the Traditionally Developed Machine Learning Techniques; 1.2.3 Structured Database with Kernel; 1.3 Distributed Database with Kernel; 1.3.1 Multiple Database Representation; 1.3.2 Kernel Selections Among Heterogeneous Multiple Databases; 1.3.3 Multiple Database Representation KA Applications to Distributed Databases; 1.4 Kernel Online Learning.
1.4.1 Kernel-Based Online Learning Algorithms1.4.2 Adopt ""Online"" KA Framework into the Traditionally Developed Machine Learning Techniques; 1.4.3 Relationship Between Online Learning and Prediction Techniques; 1.5 Prediction with Kernels; 1.5.1 Linear Prediction; 1.5.2 Kalman Filter; 1.5.3 Finite-State Model; 1.5.4 Autoregressive Moving Average Model; 1.5.5 Comparison of Four Models; 1.6 Future Direction and Conclusion; References; Chapter 2 Offline Kernel Analysis; 2.1 Introduction; 2.2 Kernel Feature Analysis; 2.2.1 Kernel Basics; 2.2.2 Kernel Principal Component Analysis (KPCA).
2.2.3 Accelerated…
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