"Multiclass imbalanced (adaboost.m1)"

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

  October 2009

  Hi,
  I will post an example process below, but in general you replace the learner by one of the operators for meta learning. They can be found in Learner/Supervised/Meta in the new Operator tag. Then you decide which inner learner you are going to use, for example a decision stump. You will put this as inner operator of the meta learner. The example process show how this works:

  <operator name="Root" class="Process" expanded="yes">
      <operator name="ExampleSetGenerator" class="ExampleSetGenerator">
          <parameter key="target_function"	value="sum classification"/>
      </operator>
      <operator name="XValidation" class="XValidation" expanded="yes">
          <operator name="AdaBoost" class="AdaBoost" expanded="yes">
              <operator name="NaiveBayes" class="NaiveBayes">
              </operator>
          </operator>
          <operator name="OperatorChain" class="OperatorChain" expanded="yes">
              <operator name="ModelApplier" class="ModelApplier">
                  <list key="application_parameters">
                  </list>
              </operator>
              <operator name="Performance" class="Performance">
              </operator>
          </operator>
      </operator>
  </operator>
  

  Greetings,
    Sebastian

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  m_r_nour Member Posts: 35 Maven

  October 2009

  thanks a lot

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