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Classification

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					Classification as data
   mining tool
         Done by
     William Hellela
      Rauf Gadar
     Alex Prewett
                Definition
   Classification is the process of
    dividing a dataset into mutually
    exclusive groups so that the
    members of each group are as
    "close" as possible to one another,
    and different groups are as "far" as
    possible from one another, where
    distance is measured with respect to
    specific variable (s) we are trying to
    predict.
          Business Examples
   A typical classification problem is to
    divide a database of companies into
    groups that are as homogeneous as
    possible with respect to a
    creditworthiness variable with values
    "Good" and "Bad“
    Predicting the response to direct
    marketing campaign [will/ will not
    respond]
    Classification vs. Regression
   What distinguishes classification from
    regression is the type of output that
    is predicted. Classification, as the
    name implies, predicts class
    membership.
    For example, a classification model
    predicts that a potential customer
    will respond to an offer.
    Classification vs. Regression
                 (cont)
   However, regression model predicts
    a specific value. For example, a
    model predicts that a certain
    customer profitability will be $854
      Predictive vs. Descriptive
               Models
   Predictive: forecast explicit values,
    based on patterns determined from
    known results.

    Descriptive: describe the patterns in
    existing data, and are generally used
    to create meaningful subgroups.
Data Mining Models
    Classification VS Other tools
   Classification is used to answer
    questions form a finite set of classes
   Estimation is used to answer
    questions from an unknown,
    continuous set of answers
   Clustering also does not require a
    finite set of predefined classes
   Prediction is a task of learning a
    pattern from examples using a
    developed model.
Questions or comments



       Any Questions ?

				
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posted:1/21/2012
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