🦉 🎤   RapidMiner Wisdom 2020 - CALL FOR SPEAKERS   🦉 🎤

We are inviting all community members to submit proposals to speak at Wisdom 2020 in Boston.


Whether it's a cool RapidMiner trick or a use case implementation, we want to see what you have.
Form link is below and deadline for submissions is November 15. See you in Boston!

CLICK HERE TO GO TO ENTRY FORM

"Multiclass imbalanced (adaboost.m1)"

m_r_nourm_r_nour Member Posts: 35  Guru
edited June 12 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
Tagged:

Answers

  • landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,527   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
Sign In or Register to comment.