INDEX 515
K
K2, 278
Kappa statistic, 163–164
kD-trees, 130–132, 136
Kepler’s three laws of planetary motion, 180
kernel
defined, 235
perceptron, 223
polynomial, 218
RBF, 219
sigmoid, 219
kernel density estimation, 97
kernel logistic regression, 223
kernel perceptron, 222–223
k-means, 137–138
k-nearest-neighbor method, 78
Knowledge Flow interface, 427–435
configuring/connecting components,
431–433
evaluation components, 430, 431
incremental learning, 433–435
starting up, 427
visualization components, 430–431
knowledge representation, 61–82
association rules, 69–70.See alsoassociation
rules
classification rules, 65–69.See also
classification rules
clusters, 81–82.See alsoclustering
decision table, 62
decision tree, 62–65.See alsodecision tree
instance-based representation, 76–80
rules involving relations, 73–75
rules with exceptions, 70–73, 210–213
trees for numeric prediction, 76
KStar, 413L
labor negotiations data, 17–18, 19
language bias, 32–33
language identification, 353
Laplace, Pierre, 91
Laplace estimator, 91, 267, 269
large datasets, 346–349
law of diminishing returns, 347lazy classifiers in Weka, 405, 413–414
LBR, 414
learning, 7–9
learning algorithms in Weka, 403–404
algorithm, listed, 404–405
Bayesian classifier, 403–406
functions, 404–405, 409–410
lazy classifiers, 405, 413–414
miscellaneous classifiers, 405, 414
neural network, 411–413
rules, 404, 408–409
trees, 404, 406–408
learning rate, 229, 230
least-absolute-error regression, 220
LeastMedSq, 409–410
leave-one-out cross-validation, 151–152
levels of measurement, 50
level-0 model, 332
level-1 model, 332
Leverage, 420
Lift, 420
lift chart, 166–168, 172
lift factor, 166
linear classification, 121–128
linearly separable, 124
linear machine, 142
linear models, 119–128, 214–235
backpropagation, 227–233
computational complexity, 218
kernel perceptron, 222–223
linear classification, 121–128
linear regression, 119–121
logistic regression, 121–125
maximum margin hyperplane, 215–217
multilayer perceptrons, 223–226, 231, 233
nonlinear class boundaries, 217–219
numeric prediction, 119–120
overfitting, 217–218
perceptron, 124–126
RBF network, 234
support vector regression, 219–222
Winnow, 126–128
linear regression, 77, 119–121
LinearRegression, 387, 409
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