[R] [R-pkgs] RMOA data stream modelling using MOA (Massive Online Analysis)

Jan Wijffels
Fri, 19 Sep 2014 12:01:28 -0000

Dear R community,

For users interested in streaming classification or building classification
models with limited amounts of RAM on your whole data set, I would like to
announce the release of a new package called RMOA on CRAN (
http://cran.r-project.org/web/packages/RMOA).

MOA is the most popular open source framework for data stream mining and is
being developed at the University of Waikato: http://moa.cms.waikato.ac.nz.
RMOA interfaces with MOA version 2014.04 and focusses on building streaming
classification & regression models on data streams (the stream package in R
already allows clustering).

Classification models which are possible through RMOA are:

- Classification trees:
  * AdaHoeffdingOptionTree
  * ASHoeffdingTree
  * DecisionStump
  * HoeffdingAdaptiveTree
  * HoeffdingOptionTree
  * HoeffdingTree
  * LimAttHoeffdingTree
  * RandomHoeffdingTree
- Bayesian classification:
  * NaiveBayes
  * NaiveBayesMultinomial
- Active learning classification:
  * ActiveClassifier
- Ensemble (meta) classifiers:
  * Bagging
      + LeveragingBag
      + OzaBag
      + OzaBagAdwin
      + OzaBagASHT
  * Boosting
      + OCBoost
      + OzaBoost
      + OzaBoostAdwin
  * Stacking
      + LimAttClassifier
  * Other
      + AccuracyUpdatedEnsemble
      + AccuracyWeightedEnsemble
      + ADACC
      + DACC
      + OnlineAccuracyUpdatedEnsemble
      + TemporallyAugmentedClassifier
      + WeightedMajorityAlgorithm

Interfaces are implemented to model data in standard files (csv, txt,
delimited), ffdf data (from the ff package), data.frames and matrices.

Documentation of MOA directed towards RMOA users can be found at
http://jwijffels.github.io/RMOA/
Examples on the use of RMOA can be found in the documentation, on github at
https://github.com/jwijffels/RMOA or e.g. by viewing the showcase at
http://bnosac.be/index.php/blog/32-rmoa-massive-online-data-stream-classifications-with-r-a-moa

I you have any remarks or requests, don't hesitate to get into contact.

stream on,
Jan


Jan Wijffels
Statistical Data Miner
www.bnosac.be  | +32 486 611708

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