03063nam 2200445 450 991056829680332120221126183411.09789811903984(electronic bk.)9789811903977(MiAaPQ)EBC6975910(Au-PeEL)EBL6975910(CKB)21957563100041(OCoLC)1314619055(PPN)269155023(EXLCZ)992195756310004120221126d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierKernel Methods for Machine Learning with Math and RaKernel methods for machine learning with math and R 100 exercises for building logic /Joe SuzukiGateway East, Singapore :Springer,[2022]©20221 online resource (203 pages)Print version: Suzuki, Joe Kernel Methods for Machine Learning with Math and R Singapore : Springer,c2022 9789811903977 Includes bibliographical references and index.Intro -- Preface -- How to Overcome Your Kernel Weakness -- What Makes KMMR Unique? -- Acknowledgments -- Contents -- 1 Positive Definite Kernels -- 1.1 Positive Definiteness of a Matrix -- 1.2 Kernels -- 1.3 Positive Definite Kernels -- 1.4 Probability -- 1.5 Bochner's Theorem -- 1.6 Kernels for Strings, Trees, and Graphs -- Appendix -- Exercises 1 sim 15 -- 2 Hilbert Spaces -- 2.1 Metric Spaces and Their Completeness -- 2.2 Linear Spaces and Inner Product Spaces -- 2.3 Hilbert Spaces -- 2.4 Projection Theorem -- 2.5 Linear Operators -- 2.6 Compact Operators -- Appendix: Proofs of Propositions -- Exercises -- 3 Reproducing Kernel Hilbert Space -- 3.1 RKHSs -- 3.2 Sobolev Space -- 3.3 Mercer's Theorem -- Appendix -- Exercises -- 4 Kernel Computations -- 4.1 Kernel Ridge Regression -- 4.2 Kernel Principle Component Analysis -- 4.3 Kernel SVM -- 4.4 Spline Curves -- 4.5 Random Fourier Features -- 4.6 Nyström Approximation -- 4.7 Incomplete Cholesky Decomposition -- Appendix -- Exercises 46sim64 -- 5 The MMD and HSIC -- 5.1 Random Variables in RKHSs -- 5.2 The MMD and Two-Sample Problem -- 5.3 The HSIC and Independence Test -- 5.4 Characteristic and Universal Kernels -- 5.5 Introduction to Empirical Processes -- Appendix -- 6 Gaussian Processes and Functional Data Analyses -- 6.1 Regression -- 6.2 Classification -- 6.3 Gaussian Processes with Inducing Variables -- 6.4 Karhunen-Lóeve Expansion -- 6.5 Functional Data Analysis -- Appendix -- Exercises 83sim100 -- Appendix Bibliography.R (Computer program language)Kernel functionsR (Computer program language)Kernel functions.006.31Suzuki Joe846228MiAaPQMiAaPQMiAaPQ9910568296803321Kernel Methods for Machine Learning with Math and RaKernel methods for machine learning with math and R2965121UNINA