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"Multiclass imbalanced (adaboost.m1)"

m_r_nourm_r_nour Member Posts: 35  Guru
edited June 2019 in Help
Hi all

I'm new in rapid miner


How can I use adaboost,m1 to deal with an imbalanced multiclass problem.

I'd appreciate if you help me in this case


Regards
REZA
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Answers

  • landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,529   Unicorn
    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
  • m_r_nourm_r_nour Member Posts: 35  Guru
    thanks a lot :D
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