"Multiclass imbalanced (adaboost.m1)"

m_r_nour

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

land

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_nour

thanks a lot