LEADER 02840nam 2200469 450 001 996464436203316 005 20220723142158.0 010 $a981-16-1438-5 035 $a(CKB)5470000001298887 035 $a(MiAaPQ)EBC6796475 035 $a(Au-PeEL)EBL6796475 035 $a(OCoLC)1282008216 035 $a(PPN)258301066 035 $a(EXLCZ)995470000001298887 100 $a20220723d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSparse estimation with math and Python $e100 exercises for building logic /$fJoe Suzuki 210 1$aGateway East, Singapore :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (254 pages) 311 $a981-16-1437-7 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- What makes SEMP unique? -- Contents -- 1 Linear Regression -- 1.1 Linear Regression -- 1.2 Subderivative -- 1.3 Lasso -- 1.4 Ridge -- 1.5 A Comparison Between Lasso and Ridge -- 1.6 Elastic Net -- 1.7 About How to Set the Value of ? -- 2 Generalized Linear Regression -- 2.1 Generalization of Lasso in Linear Regression -- 2.2 Logistic Regression for Binary Values -- 2.3 Logistic Regression for Multiple Values -- 2.4 Poisson Regression -- 2.5 Survival Analysis -- 3 Group Lasso -- 3.1 When One Group Exists -- 3.2 Proxy Gradient Method -- 3.3 Group Lasso -- 3.4 Sparse Group Lasso -- 3.5 Overlap Lasso -- 3.6 Group Lasso with Multiple Responses -- 3.7 Group Lasso Via Logistic Regression -- 3.8 Group Lasso for the Generalized Additive Models -- 4 Fused Lasso -- 4.1 Applications of Fused Lasso -- 4.2 Solving Fused Lasso Via Dynamic Programming -- 4.3 LARS -- 4.4 Dual Lasso Problem and Generalized Lasso -- 4.5 ADMM -- 5 Graphical Models -- 5.1 Graphical Models -- 5.2 Graphical Lasso -- 5.3 Estimation of the Graphical Model Based on the Quasi-Likelihood -- 5.4 Joint Graphical Lasso -- 6 Matrix Decomposition -- 6.1 Singular Decomposition -- 6.2 Eckart-Young's Theorem -- 6.3 Norm -- 6.4 Sparse Estimation for Low-Rank Estimations -- 7 Multivariate Analysis -- 7.1 Principal Component Analysis (1): SCoTLASS -- 7.2 Principle Component Analysis (2): SPCA -- 7.3 K-Means Clustering -- 7.4 Convex Clustering -- Appendix References. 606 $aMultivariate analysis 606 $aEstimation theory 606 $aPython (Computer program language) 615 0$aMultivariate analysis. 615 0$aEstimation theory. 615 0$aPython (Computer program language) 676 $a519.535 700 $aSuzuki$b Joe$0846228 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464436203316 996 $aSparse Estimation with Math and Python$92569690 997 $aUNISA