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• Classic-Fiction

cube computation and193

data cube110–111

at multiple granularities230–231

multiway array195–199

simultaneous193, 195

AGNES. seeAgglomerative Nesting

algebraic measures145

algorithms.

all_confidence measure268, 272

all-versus-all (AVA)430–431

analysis of variance (ANOVA)600

analytical processing153

ancestor cells189

angle-based outlier detection (ABOD)580

angle-based outlier factor (ABOF)580

anomalies. seeoutliers

anomaly mining. seeoutlier analysis

anomaly-based detection614

antimonotonic constraints298, 301

antimonotonic measures194

antimonotonicity249

apex cuboids111, 138, 158

application domain-specific semantics282

applications33, 607–618

business intelligence27

computer science613

domain-specific625

engineering613, 624

exploration623

financial data analysis607–609

intrusion detection/prevention614–615

recommender systems615–618

retail industry609–611

science611–613

social science and social studies613

targeted27–28

telecommunications industry611

Web search engines28

application-specific outlier detection548–549

approximate patterns281

mining307–312

Apriori algorithm248–253, 272

dynamic itemset counting256

efficiency, improving254–256

example250–252

hash-based technique255

join step249

partitioning255–256

prune step249–250

pseudocde253

sampling256

transaction reduction255

Apriori property194, 201, 249

antimonotonicity249

in Apriori algorithm298

Apriori pruning method194

arrays

3-D for dimensions196

sparse compression198–199

association analysis17–18

association rules245

approximate281

Boolean281

compressed281

confidence21, 245, 246, 416

constraint-based281

constraints296–297

correlation265, 272

discarded17

fittest426

frequent patterns and280

generation from frequent itemsets253, 254

hybrid-dimensional288

interdimensional288

intradimensional287

metarule-guided mining of295–296

minimum confidence threshold18, 245

minimum support threshold245

mining272

multidimensional17, 287–289, 320

multilevel281, 283–287, 320

near-match281

objective measures21

offspring426

quantitative281, 289, 320

redundancy-aware top-k281

single-dimensional17, 287

spatial595

strong264–265, 272

support21, 245, 246, 417

top-k281

types of values in281

associative classification415, 416–419, 437

CBA417

CMAR417–418

CPAR418–419

rule confidence416

rule support417

steps417

asymmetric binary dissimilarity71

asymmetric binary similarity71

attribute construction112

accuracy and105

multivariate splits344

attribute selection measures331, 336–344

CHAID343

gain ratio340–341

Gini index341–343

information gain336–340

Minimum Description Length (MDL)343–344

multivariate splits343–344

attribute subset selection100, 103–105

decision tree induction105

forward selection/backward elimination combination105

greedy methods104–105

stepwise backward elimination105

stepwise forward selection105

attribute vectors40, 328

attribute-oriented induction (AOI)166–178, 180

algorithm173

for class comparisons175–178

for data characterization167–172

data generalization by166–178

generalized relation172

implementation of172–174

attributes9, 40

abstraction level differences99

behavioral546, 573

binary41–42, 79

Boolean41

categorical41

class label328

contextual546, 573

continuous44

correlated54–56

dimension correspondence10

discrete44

generalization169–170

generalization control170

generalization threshold control170

grouping231

interval-scaled43, 79

of mixed type75–77

nominal41, 79

numeric43–44, 79

ordered103

ordinal41, 79

qualitative41

ratio-scaled43–44, 79

reducts of427

removal169

repetition346

set of118

splitting333

terminology for40

type determination41

types of39

unordered103

audio data mining604–607, 624

automatic classification445

AVA. seeall-versus-all

AVC-group347

AVC-set347