Int Prediction

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  land RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn

  March 2009

  Hi Jorge,
  you could transform this problem into a regression problem by changing the label into a numerical attribute. The regression learners predict a number and not a discret number of classes, so even if a value is not included, it can be returned.
  Most regression learners do not cope with nominal values, so you might have to binomalise them.
  
  Greetings,
    Sebastian

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  Jorge Member Posts: 19 Maven

  March 2009

  Thanks Sebastian,
  
  But the regression learners (as far I know) make operations with the values of the atributtes, and they give different results if the transformation to binomial values is different.
  
  An example:
  
  attr1: a --> 0
  attr1: b --> 1
  attr1: c --> 2
  
  gives result 1
  
  and:
  
  attr1: a --> 2
  attr1: b --> 1
  attr1: c --> 0
  
  gives result 2
  
  And result 1, result 2 are differents
  
  Am I wrong?
  
  Thanks another time,
  Jorge
  

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  keith Member Posts: 157 Maven

  March 2009

  I think what Sebastian meant is to create binomial variables for each possible value of an attribute that is 1 (TRUE) if the attribute is that value, and 0 (FALSE) otherwise.
  
  e.g.
  
  if attr1 can have values a, b, or c, then you create three variables:
  
  attr1_is_a = 0/1
  attr1_is_b = 0/1
  attr1_is_c = 0/1
  
  So if you have three rows, each with different values for attr1, the three new variables would take on values of:
  
  attr1 : { attr1_is_a, attr1_is_b, attr1_is_c }
  a : { 1, 0, 0 }
  b : { 0, 1, 0 }
  c : { 0, 0, 1 }
  
  Hope this helps.
  
  Keith
  

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