Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications

INDEX

3D visualizations, 51

Absorption, Distribution, Metabolism, Excretion, 179

Active interaction, see Interaction design techniques, active

Adjusted R², 141–142, 264

ADME, see Absorption, Distribution, Metabolism, Excretion

Agglomerative hierarchical clustering, 59, 87–98, 183, 185, 213, 254–255

average linkage, 88, 93–96, 254

centroid, 96

complete linkage, 88, 92–93, 95, 183, 254

distance cut-off, 97–98, 255

process, 88

selecting groups, 96–98

single linkage, 88–92, 95, 254

Wards, 96

Aggregated, 234–235. See also Transformation

Alignment, see Visual features, alignment; Graphics design, visual grouping

Alternative hypothesis, see Hypothesis test, alternative hypothesis

Analysis, see Data mining process, analysis

Analysis of variance, 246, 251–252, 264–265

Analytics, 213. See also Data mining

ANOVA, see Analysis of variance

Applicability domain, 179

Applications, 16, 67, 165–214

acquiring new customers, 165, 167

advertisement, 175–176

assessing credit risk, 166, 170, 174, 192–203

cross-selling, 168–169, 172–173

enhancing product design, 174

entertainment, 175–176

financials, 169–170, 214

government, 176–177

growing business, 168, 171

healthcare, 179–180, 214

identifying criminal activities, 166, 169–170, 172, 174, 176–177

identifying health risks, 171, 179–180

identifying new products, 171

improving underwriting, 171–172

insurance, 145, 171–172

manufacturing, 174–175, 214

marketing campaigns, 166–169

mining trading data, 170

modeling customer experience, 168

operational efficiency, ...