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研究生：	王麒瑋 Wang, Chea-Wei
論文名稱：	支向機核心函數適用指標之建立 Index of Kernel Functions for Support Vector Machine
指導教授：	利德江 Li, Der-Chang
學位類別：	碩士 Master
系所名稱：	管理學院 - 工業管理科學系 Department of Industrial Management Science
論文出版年：	2003
畢業學年度：	91
語文別：	英文
論文頁數：	44
外文關鍵詞：	index of kernel function, support vector machines., Clustering
相關次數：	點閱：142 下載：0
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A Support Vector Machine (SVM) is a learning machine of novel type, based on statistical learning framework. It has become an increasingly popular tool for machine learning tasks such as classification, regression or novelty detection. To increase learning accuracy of a SVM, kernel plays an important role. This research aims at finding an index of kernels for support vector machines. Used simulation data are produced following Dirichlet and normal distributions. A real experiment for choosing kernel functions is also provided.

ABLE OF CONTENTS
ABSTRACT  ……………….……………………………………………………………..i
ACKNOWLEDGEMENTS  …………………...………………………………………ii
TABLE OF CONTENTS  …………………………………………………………….iii
LIST OF FIGURES  …...………………………………………………………….……..v
LIST OF F IGURES  ..…...………………………………………………………….…..vi
CHAPTER 1  INTRODUCTION  ……………………………………………….1
    1.1  Motivation  ……………………………………………………………….2
    1.2  Objectives and Approach ………………………………………………………3
CHAPTER 2  LITERATURE REVIEW  ………………………………………………….4
    2.1  Support Vector Machine  ……………………………………………………..4
    2.2  Extend of Support Vector Machine  ….…………………………………….10
        2.2.1 One-class Support Vector Machine (Distribution Estimation) ……..10
        2.2.2 Support Vector Regression  …….……………………………………11
    2.3  Applications of Support Vector Machine ……………………………………..13
CHAPTER 3  INDEX OF KERNEL FUNCTIONS  …………………………..……15
    3.1  Kernel Functions of Support Vector Machine …………………..……...…..15
        3.3.1 Polynomial Kernel Function   ……………………………………….…16
        3.3.2 Radial Basis Function (RBF )……...……………………………….….…17
        3.3.3 Sigmoid Kernel Function  ……….………………………………….…..17
    3.2  Mess Level  ...………………………………………………………………...18
CHAPTER 4  	EXPERIMENTAL STUDY ……………………………………...22
    4.1  Normal Distribution  ……………………………………………………….24
    4.2  Dirichlet Distribution  ……………………………………………………….24
        4.2.1 Generating Dirichlet Distribution   ……………………………………25
    4.3  Index Establishing ……….………………………………………………..27
    4.4  Experimental Cases ………………………………………………………..35
CHAPTER 5  	DISCUSSIONS AND SUGGESTIONS ….………………37
REFERENCE ………………………………………….…………………….…39
APPENDIX The Description of pima Data Set …………….……………….……...41
                                    

REFERENCES
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校內：立即公開
校外：2003-06-30公開

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