What is included with this book?
Preface | p. V |
Technical Notes | p. XIII |
List of Figures | p. XV |
Introduction | p. 1 |
Data visualization: beyond the third dimension | p. 1 |
Statistical data visualization: goals and history | p. 3 |
Getting down to data | p. 4 |
Getting real: process and caveats | p. 8 |
Interactive investigation | p. 15 |
The Toolbox | p. 17 |
Introduction | p. 17 |
Plot types | p. 19 |
Univariate plots | p. 19 |
Bivariate plots | p. 21 |
Multivariate plots | p. 24 |
Plot arrangement | p. 34 |
Plot manipulation and enhancement | p. 35 |
Brushing | p. 35 |
Identification | p. 41 |
Scaling | p. 41 |
Subset selection | p. 42 |
Line segments | p. 43 |
Interactive drawing | p. 43 |
Dragging points | p. 43 |
Tools available elsewhere | p. 44 |
Recap | p. 45 |
Exercises | p. 45 |
Missing Values | p. 47 |
Background | p. 48 |
Exploring missingness | p. 49 |
Shadow matrix | p. 49 |
Getting started: missings in the "margins" | p. 52 |
A limitation | p. 53 |
Tracking missings using the shadow matrix | p. 55 |
Imputation | p. 55 |
Mean values | p. 56 |
Random values | p. 56 |
Multiple imputation | p. 58 |
Recap | p. 61 |
Exercises | p. 62 |
Supervised Classification | p. 63 |
Background | p. 64 |
Classical multivariate statistics | p. 65 |
Data mining | p. 66 |
Studying the fit | p. 69 |
Purely graphics: getting a picture of the class structure | p. 70 |
Overview of Italian Olive Oils | p. 70 |
Building classifiers to predict region | p. 71 |
Separating the oils by area within each region | p. 73 |
Taking stock | p. 77 |
Numerical methods | p. 77 |
Linear discriminant analysis | p. 77 |
Trees | p. 81 |
Random forests | p. 83 |
Neural networks | p. 88 |
Support vector machine | p. 92 |
Examining boundaries | p. 97 |
Recap | p. 99 |
Exercises | p. 99 |
Cluster Analysis | p. 103 |
Background | p. 105 |
Purely graphics | p. 107 |
Numerical methods | p. 111 |
Hierarchical algorithms | p. 111 |
Model-based clustering | p. 113 |
Self-organizing maps | p. 119 |
Comparing methods | p. 122 |
Characterizing clusters | p. 125 |
Recap | p. 126 |
Exercises | p. 127 |
Miscellaneous Topics | p. 129 |
Inference | p. 129 |
Longitudinal data | p. 134 |
Network data | p. 139 |
Multidimensional scaling | p. 145 |
Exercises | p. 151 |
Datasets | p. 153 |
Tips | p. 153 |
Australian Crabs | p. 154 |
Italian Olive Oils | p. 155 |
Flea Beetles | p. 157 |
PRIM7 | p. 157 |
Tropical Atmosphere-Ocean Array (TAO) | p. 159 |
Primary Biliary Cirrhosis (PBC) | p. 161 |
Spam | p. 162 |
Wages | p. 164 |
Rat Gene Expression | p. 166 |
Arabidopsis Gene Expression | p. 168 |
Music | p. 171 |
Cluster Challenge | p. 172 |
Adjacent Transposition Graph | p. 172 |
Florentine Families | p. 173 |
Morse Code Confusion Rates | p. 174 |
Personal Social Network | p. 175 |
References | p. 177 |
Index | p. 185 |
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