\BOOKMARK [0][-]{chapter.1}{Setting the Stage}{}% 1
\BOOKMARK [1][-]{section.1.1}{What Are Recommender Systems?}{chapter.1}% 2
\BOOKMARK [1][-]{section.1.2}{How Is It Done?}{chapter.1}% 3
\BOOKMARK [2][-]{subsection.1.2.1}{Nearest-Neighbor Methods}{section.1.2}% 4
\BOOKMARK [2][-]{subsection.1.2.2}{Latent Factor Approach: Matrix Factorization}{section.1.2}% 5
\BOOKMARK [2][-]{subsection.1.2.3}{Latent Factor Approach: Statistical Models}{section.1.2}% 6
\BOOKMARK [3][-]{subsubsection.1.2.3.1}{Comparison}{subsection.1.2.3}% 7
\BOOKMARK [1][-]{section.1.3}{Covariates/Side Information}{chapter.1}% 8
\BOOKMARK [1][-]{section.1.4}{Prerequisites}{chapter.1}% 9
\BOOKMARK [1][-]{section.1.5}{Software}{chapter.1}% 10
\BOOKMARK [1][-]{section.1.6}{What You Should Gain from This Book}{chapter.1}% 11
\BOOKMARK [0][-]{chapter.2}{Some Infrastructure: Linear Algebra}{}% 12
\BOOKMARK [1][-]{section.2.1}{Matrix Rank and Vector Linear Independence}{chapter.2}% 13
\BOOKMARK [1][-]{section.2.2}{Partitioned Matrices}{chapter.2}% 14
\BOOKMARK [2][-]{subsection.2.2.1}{How It Works}{section.2.2}% 15
\BOOKMARK [2][-]{subsection.2.2.2}{Important Special Case}{section.2.2}% 16
\BOOKMARK [1][-]{section.2.3}{The Notion of Approximate Rank: Principal Components Analysis}{chapter.2}% 17
\BOOKMARK [2][-]{subsection.2.3.1}{Dimension Reduction}{section.2.3}% 18
\BOOKMARK [2][-]{subsection.2.3.2}{Exploiting Correlations}{section.2.3}% 19
\BOOKMARK [2][-]{subsection.2.3.3}{Eigenanalysis}{section.2.3}% 20
\BOOKMARK [2][-]{subsection.2.3.4}{PCA}{section.2.3}% 21
\BOOKMARK [2][-]{subsection.2.3.5}{Matrix View}{section.2.3}% 22
\BOOKMARK [2][-]{subsection.2.3.6}{Why It Works}{section.2.3}% 23
\BOOKMARK [2][-]{subsection.2.3.7}{Choosing the Number of Principal Components}{section.2.3}% 24
\BOOKMARK [2][-]{subsection.2.3.8}{Software and Example}{section.2.3}% 25
\BOOKMARK [0][-]{chapter.3}{Some Infrastructure: Probability and Statistics}{}% 26
\BOOKMARK [1][-]{section.3.1}{Data as a Sample}{chapter.3}% 27
\BOOKMARK [1][-]{section.3.2}{Probability, Expected Value and Variance}{chapter.3}% 28
\BOOKMARK [1][-]{section.3.3}{Regression Models}{chapter.3}% 29
\BOOKMARK [2][-]{subsection.3.3.1}{Definition}{section.3.3}% 30
\BOOKMARK [2][-]{subsection.3.3.2}{Prediction}{section.3.3}% 31
\BOOKMARK [2][-]{subsection.3.3.3}{Estimation}{section.3.3}% 32
\BOOKMARK [3][-]{subsubsection.3.3.3.1}{Nonparametric}{subsection.3.3.3}% 33
\BOOKMARK [3][-]{subsubsection.3.3.3.2}{Parametric}{subsection.3.3.3}% 34
\BOOKMARK [3][-]{subsubsection.3.3.3.3}{Comparison}{subsection.3.3.3}% 35
\BOOKMARK [2][-]{subsection.3.3.4}{The lm\(\) Function in R}{section.3.3}% 36
\BOOKMARK [2][-]{subsection.3.3.5}{Details of Linear Regression Estimation}{section.3.3}% 37
\BOOKMARK [3][-]{subsubsection.3.3.5.1}{Polynomial Terms}{subsection.3.3.5}% 38
\BOOKMARK [2][-]{subsection.3.3.6}{Categorical Variables \(Predictor, Response\)}{section.3.3}% 39
\BOOKMARK [3][-]{subsubsection.3.3.6.1}{Dummy Variables as Predictors}{subsection.3.3.6}% 40
\BOOKMARK [3][-]{subsubsection.3.3.6.2}{Interaction Terms}{subsection.3.3.6}% 41
\BOOKMARK [3][-]{subsubsection.3.3.6.3}{Dummy Variables as Response Variables}{subsection.3.3.6}% 42
\BOOKMARK [2][-]{subsection.3.3.7}{R's predict\(\), a Generic Function}{section.3.3}% 43
\BOOKMARK [2][-]{subsection.3.3.8}{More Than Two Levels in Categorical Response}{section.3.3}% 44
\BOOKMARK [1][-]{section.3.4}{Bias, Variance, Overfitting and p-Hacking}{chapter.3}% 45
\BOOKMARK [2][-]{subsection.3.4.1}{What Is Overfitting?}{section.3.4}% 46
\BOOKMARK [2][-]{subsection.3.4.2}{Can Anything Be Done about It?}{section.3.4}% 47
\BOOKMARK [2][-]{subsection.3.4.3}{The Problem of P-hacking}{section.3.4}% 48
\BOOKMARK [1][-]{section.3.5}{Extended Example}{chapter.3}% 49
\BOOKMARK [0][-]{chapter.4}{Nearest-Neighbor Methods}{}% 50
\BOOKMARK [1][-]{section.4.1}{Notation}{chapter.4}% 51
\BOOKMARK [1][-]{section.4.2}{User-Based Filtering}{chapter.4}% 52
\BOOKMARK [2][-]{subsection.4.2.1}{Matrix View}{section.4.2}% 53
\BOOKMARK [2][-]{subsection.4.2.2}{\(One\) Implementation}{section.4.2}% 54
\BOOKMARK [1][-]{section.4.3}{Regression Analog}{chapter.4}% 55
\BOOKMARK [1][-]{section.4.4}{Choosing k}{chapter.4}% 56
\BOOKMARK [1][-]{section.4.5}{Defining Distance}{chapter.4}% 57
\BOOKMARK [1][-]{section.4.6}{Item-Based Filtering}{chapter.4}% 58
\BOOKMARK [1][-]{section.4.7}{Covariates}{chapter.4}% 59
\BOOKMARK [1][-]{section.4.8}{Edge Bias}{chapter.4}% 60
\BOOKMARK [0][-]{chapter.5}{Matrix Factorization Methods}{}% 61
\BOOKMARK [0][-]{chapter.6}{Statistical Models}{}% 62
\BOOKMARK [0][-]{chapter.7}{Use of Side Information}{}% 63
\BOOKMARK [0][-]{chapter.8}{Bias, Variance and Overfitting}{}% 64
\BOOKMARK [0][-]{appendix.A}{R Quick Start}{}% 65
\BOOKMARK [1][-]{section.A.1}{Correspondences}{appendix.A}% 66
\BOOKMARK [1][-]{section.A.2}{Starting R}{appendix.A}% 67
\BOOKMARK [1][-]{section.A.3}{First Sample Programming Session}{appendix.A}% 68
\BOOKMARK [1][-]{section.A.4}{Vectorization}{appendix.A}% 69
\BOOKMARK [1][-]{section.A.5}{Second Sample Programming Session}{appendix.A}% 70
\BOOKMARK [1][-]{section.A.6}{Recycling}{appendix.A}% 71
\BOOKMARK [1][-]{section.A.7}{More on Vectorization}{appendix.A}% 72
\BOOKMARK [1][-]{section.A.8}{Third Sample Programming Session}{appendix.A}% 73
\BOOKMARK [1][-]{section.A.9}{Default Argument Values}{appendix.A}% 74
\BOOKMARK [1][-]{section.A.10}{The R List Type}{appendix.A}% 75
\BOOKMARK [2][-]{subsection.A.10.1}{The Basics}{section.A.10}% 76
\BOOKMARK [2][-]{subsection.A.10.2}{The Reduce\(\) Function}{section.A.10}% 77
\BOOKMARK [2][-]{subsection.A.10.3}{S3 Classes}{section.A.10}% 78
\BOOKMARK [1][-]{section.A.11}{Some Workhorse Functions}{appendix.A}% 79
\BOOKMARK [1][-]{section.A.12}{Handy Utilities}{appendix.A}% 80
\BOOKMARK [1][-]{section.A.13}{Data Frames}{appendix.A}% 81
\BOOKMARK [1][-]{section.A.14}{Graphics}{appendix.A}% 82
\BOOKMARK [1][-]{section.A.15}{Packages}{appendix.A}% 83
\BOOKMARK [1][-]{section.A.16}{Other Sources for Learning R}{appendix.A}% 84
\BOOKMARK [1][-]{section.A.17}{Online Help}{appendix.A}% 85
\BOOKMARK [1][-]{section.A.18}{Debugging in R}{appendix.A}% 86
\BOOKMARK [1][-]{section.A.19}{Complex Numbers}{appendix.A}% 87
\BOOKMARK [1][-]{section.A.20}{Further Reading}{appendix.A}% 88