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  1. CRoss Industry Standard Process for Data Mining (http://www.crisp-dm.org/)
  2. Weka, 
    Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
  3. ARFF Output and Weka Scoring plugin for PDI, http://wiki.pentaho.com/display/EAI/List+of+Available+Pentaho+Data+Integration+Plug-Ins
  4. UCI Machine Learning Repository, http://archive.ics.uci.edu/ml/datasets.html
  5. Online Pentaho Weka Documentation, http://wiki.pentaho.com/display/DATAMINING/Pentaho+Data+Mining+Community+Documentation
  6. Pentaho Weka Forum, http://forums.pentaho.org/forumdisplay.php?f=81
  7. A complete online statistics handbook, http://www.statsoft.com/textbook/
  8. Homepage of Data Miners Inc, The authors of four Wiley books on data mining, Michael Berry and Gordon Linoff, www.data-miners.com
  9. Data mining community, www.kdnuggets.com