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I aim to have some anomaly detection process on my data but Weka, Rapidminer or Knime do not support anomaly detection algorithms. How would I take care of the process?

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Use ELKI. It not only has tons of anomaly detection algorithms (they call them "outlier detection" though), but it also is significantly faster than the others, in particular when you used indexes.

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    $\begingroup$ but Anony , ELKI dont have any outlier detection algorithm in time series domain. they are almost all work for clustering high dimensional data , not for time series data. Erogol want outlier detection algorithm in time series domain. Which in fact, i am also figuring out , so Erogol , have have you found any algorithm in time series domain. Thanks $\endgroup$
    – sash
    Jul 15 '13 at 15:08
  • $\begingroup$ Where is "time series" in his question? $\endgroup$ Jul 16 '13 at 8:18
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For Venturini's (2011) outlier detection method Washer, its inventor published an R implementation here and an R package here.

Venturini, A. (2011). Time Series Outlier Detection: A New Non Parametric Methodology (Washer). Statistica 71: 329-344.

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    $\begingroup$ @ Dr Jochen L. Leidner -its considered good form to post some details of any links you supply, so that the answer can remain useful even if the link is broken. Welcome to the site $\endgroup$ Nov 14 '12 at 18:54
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R has a full task view listing the major implementations.

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