Tuesday, May 10, 2011

Data mining (1)

  • Data mining is more clear to be called “knowledge mining from data”. Knowledge extraction, data/pattern analysis.
  • The knowledge extraction/discovery is a sequence of:
    1. Data cleaning (remove noise and inconsistent data)
    2. Data integration (from multi sources)
    3. Data selection
    4. Data transformation ( to specific form)
    5. Data mining (extract data pattern)
    6. Patter evaluation
    7. Knowledge presentation
  • Classification is the process of finding a model/function that describes and distinguishes data classes/concepts, for the purpose of being able too use the model to predict the class of objects whose class label is unknown. The derived model is based on the analysis of a set of training data whose class label is known.
  • Cluster analysis. Unlike classification and prediction, which analyze class-labeled data, clustering analyzes data objects without knowing a known class label.
  • Data preparing, such as data normalization.

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