Index

At the end of each week is an index of topics covered that week.

A full index to the course appears under DOWNLOADS, below.

Topic   Step
Datasets airline 1.7, 1.8, 1.9, 1.10, 1.11, 1.12, 1.13
  appleStocks 1.13
  Financial data for GOOG 1.14
  Infrared data from soil samples 1.16, 1.18
  sentiment 1.4
  Soil dataset (org_c_n) 1.18
  wine 1.15
Classifiers LinearRegression 1.7, 1.9, 1.10, 1.11, 1.15, 1.18
  M5P 1.18
  NaiveBayesMultinomial 1.4
  OneR 1.4
  RandomForest 1.18
  REPTree 1.18
  SMOreg 1.8, 1.10, 1.11
  ZeroR 1.4
Metalearners FilteredClassifier 1.9
Filters AddExpression 1.8
  Copy 1.7
  Remove 1.9
  RemoveMisclassified 1.4
  RemoveRange 1.7, 1.8
  Resample 1.4
  TimeSeriesTranslate 1.7, 1.8
Packages timeseriesForecasting 1.9
Plus … Downsampling 1.18
  Forecast panel 1.9, 1.10, 1.11, 1.12
  International Conf. on Machine Learning (ICML) 1.16
  Lagged variables 1.6–1.15
  Overlay data 1.13
  Row normalization 1.18
  Savitzky-Golay smoothing 1.18
  Time series analysis 1.6–1.15

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This article is from the free online course:

Advanced Data Mining with Weka

The University of Waikato

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