518 INDEX
numeric prediction (continued)
model tree, 244–251.See alsomodel
tree
rules, 251
stacking, 334
trees, 76, 243
NumericToBinary, 399
NumericTransform, 397O
O(n), 196
O(n^2 ), 196
Obfuscate, 396, 400
object editor, 366, 381, 393
Occam’s razor, 180, 183
oil slick detection, 23
1R procedure, 84–88, 139
OneR, 408
OneRAttributeEval, 423
one-tailed, 148
online documentation, 368
Open DB, 382
optimizing performance in Weka, 417
OptionHandler, 451, 482
option nodes, 328
option trees, 328–331
orderings
circular, 349
partial, 349
order-independent rules, 67, 112
OrdinalClassClassifier, 418
ordinal attributes, 51
ordinal quantities, 50
orthogonal, 307
outer cross-validation, 286
outliers, 313, 342
output
data engineering, 287–288, 315–341.See also
engineering input and output
knowledge representation, 61–82.See also
knowledge representation
overfitting, 86
Bayesian clustering, 268
category utility, 261
forward stagewise additive regression, 326MDL principle, 181
multilayer perceptrons, 233
1R, 87
statistical tests, 30
support vectors, 217–218
overfitting-avoidance bias, 34
overgeneralization, 239, 243
overlapping hyperrectangles, 239
overlay data, 53P
pace regression in Weka, 410
PaceRegression, 410
paired t-test, 154, 294
pairwise classification, 123, 410
pairwise coupling, 123
pairwise plots, 60
parabola, 240
parallelization, 347
parameter tuning, 286
Part, 409
partial decision tree, 207–210
partial ordering, 51
partitioning instance space, 79
pattern recognition, 39
Percentage split, 377
perceptron
defined, 126
kernel, 223
learning rule, 124, 125
linear classification, 124–126
multilayer, 223–226, 233
voted, 223
perceptron learning rule, 124, 125
permutation tests, 362
PKIDiscretize, 396, 398
Poisson distribution, 268
Polygon, 389
Polyline, 389
polynomial kernel, 218
popular music, 359
postal ZIP code, 57
postpruning, 34, 192
precision, 171
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