INDEX 509
randomization, 320–321
stacking, 332–334
command-line interface, 449–459
class, 450, 452
classifierspackage, 453–455
corepackage, 451, 452
generic options, 456–458
instance, 450
Javadoc indices, 456
package, 451, 452
scheme-specific options, 458–459
starting up, 449–450
weka.associations, 455
weka.attributeSelection, 455
weka.clusterers, 455
weka.estimators, 455
weka.filters, 455
command-line options, 456–459
comma-separated value (CSV) format, 370,
371
comparing data mining methods, 153–157
ComplementNaiveBayes, 405
compression techniques, 362
computational learning theory, 324
computeEntropy(), 480
Computer Assisted Passenger Pre-Screening
System (CAPPS), 357
computer network security, 357
computer software.SeeWeka workbench
concept, 42
concept description, 42
concept description language, 32
concept representation, 82.See alsoknowledge
representation
conditional independence, 275
conditional likelihood for scoring networks,
280, 283
confidence, 69, 113, 324
Confidence, 420
confidence tests, 154–157, 184
conflict resolution strategies, 82
confusion matrix, 163
conjunction, 65
ConjunctiveRule, 408–409
consensus filter, 342consequent, of rule, 65
ConsistencySubsetEval, 422
constrained quadratic optimization, 217
consumer music, 359
contact lens data, 6, 13–15
continuous attributes, 49.See alsonumeric
attributes
continuous monitoring, 28–29
converting discrete to numeric attributes,
304–305
convex hull, 171, 216
Conviction, 420
Copy, 395
corepackage, 451, 452
corrected resampled t-test, 157
correlation coefficient, 177–179
cost curves, 173–176
cost matrix, 164–165
cost of errors, 161–176
bagging, 319–320
cost curves, 173–176
cost-sensitive classification, 164–165
cost-sensitive learning, 165–166
Kappa statistic, 163–164
lift charts, 166–168
recall-precision curves, 171–172
ROC curves, 168–171
cost-sensitive classification, 164–165
CostSensitiveClassifier, 417
cost-sensitive learning, 165–166
cost-sensitive learning in Weka, 417
co-training, 339–340
covariance matrix, 267, 307
coverage, of association rules, 69
covering algorithm, 106–111
cow culling, 3–4, 37, 161–162
CPU performance data, 16–17
credit approval, 22–23
cross-validated ROC curves, 170
cross-validation, 149–152, 326
inner, 286
outer, 286
repeated, 144
CrossValidationFoldMaker, 428, 431
CSV format, 370, 371P088407-INDEX.qxd 4/30/05 11:25 AM Page 509