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Data Mining: Practical Machine Learning Tools and ... - LIDeCC

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INDEX 507automatic filtering, 315averaging over subnetworks, 283axis-parallel class boundaries, 242Bbackground knowledge, 348backpropagation, 227–233backtracking, 209backward elimination, 292, 294backward pruning, 34, 192bagging, 316–319Bagging, 414–415bagging with costs, 319–320bag of words, 95balanced Winnow, 128ball tree, 133–135basic methods. See algorithms-basic methodsbatch learning, 232Bayes, Thomas, 141Bayesian classifier. See Naïve BayesBayesian clustering, 268–270Bayesian multinet, 279–280Bayesian network, 141, 271–283AD tree, 280–283Bayesian multinet, 279–280caveats, 276, 277counting, 280K2, 278learning, 276–283making predictions, 272–276Markov blanket, 278–279multiplication, 275Naïve Bayes classifier, 278network scoring, 277simplifying assumptions, 272structure learning by conditionalindependence tests, 280TAN (Tree Augmented Naïve Bayes), 279Weka, 403–406Bayesian network learning algorithms, 277–283Bayesian option trees, 328–331, 343Bayesians, 141Bayesian scoring metrics, 277–280, 283Bayes information, 271BayesNet, 405Bayes’s rule, 90, 181beam search, 34, 293beam width, 34beer purchases, 27Ben Ish Chai, 358Bernoulli process, 147BestFirst, 423best-first search, 293best-matching node, 257bias, 32defined, 318language, 32–33multilayer perceptrons, 225, 226overfitting-avoidance, 34–35perceptron learning rule, 124search, 33–34what is it, 317bias-variance decomposition, 317, 318big data (massive datasets), 346–349binningequal-frequency, 298equal-interval, 298equal-width, 342binomial coefficient, 218bits, 102boolean, 51, 68boosting, 321–325, 347boosting in Weka, 416bootstrap aggregating, 318bootstrap estimation, 152–153British Petroleum, 28buildClassifier(), 453, 472, 482CC4.5, 105, 198–199C5.0, 199calm computing, 359, 362capitalization conventions, 310CAPPS (Computer Assisted Passenger Pre-Screening System), 357CART (Classification And Regression Tree), 29,38, 199, 253categorical attributes, 49. See also nominalattributescategory utility, 260–262

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