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Index

(A full index to the course appears at the end of Week 1.)

Topic   Step
Datasets Forest cover type (covtypeNorm) 2.3, 2.9, 2.12
  labelled_tweets 2.12
  NSW Electricity Market (elecNormNew) 2.5, 2.12
  Signal peptide cleavage data (sigdata) 2.13, 2.14
Classifiers HoeffdingAdaptiveTree 2.8, 2.9
  HoeffdingOptionTree 2.5
  HoeffdingTree (Weka) 2.2, 2.3, 2.5
  HoeffdingTree (MOA) 2.5, 2.6, 2.7, 2.9, 2.10
  IBk 2.3
  Incremental 2.2, 2.3
  J48 2.3, 2.13, 2.14
  MajorityClass 2.9, 2.12
  NaiveBayes 2.7, 2.9
  NaiveBayesUpdateable 2.3
  NaiveBayesMultinomial 2.10, 2.12
  SGD (Stochastic gradient descent) 2.10
  SGDText 2.12
  Updateable classifiers 2.2
Metalearners LeveragingBag 2.8, 2.9
  OzaBag 2.4, 2.5, 2.7, 2.9
  OzaBagAdwin 2.8, 2.9
Filters Resample 2.5
  StringToWordVector 2.12
Packages massiveOnlineAnalysis (MOA) 2.4, 2.5
Generators HyperplaneGenerator 2.5, 2.6
  LED24 (Weka) 2.3
  LEDGenerator (MOA) 2.4
  RandomRBFGenerator 2.8, 2.9
  RandomRBFGeneratorDrift 2.9
  WaveformGenerator 2.7
Evaluation Kappa statistic 2.7, 2.10, 2.12
  Kappa-temporal statistic 2.12
  Periodic holdout 2.6, 2.7
  Prequential 2.6, 2.7, 2.9, 2.10, 2.12
Plus … Adaptive sliding window (ADWIN) 2.8
  Bioinformatics 2.13, 2.14
  Bootstrap sampling 2.8
  Data stream mining 2.1–2.12
  MOA system 2.6–2.12
  Sequence analysis 2.13, 2.14
  Sentiment analysis 2.10, 2.11, 2.12
  Signal peptide prediction 2.13, 2.14
  Twitter 2.10, 2.11, 2.12

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Advanced Data Mining with Weka

The University of Waikato

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