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Multi label performance operator

ruhailaruhaila Member Posts: 3 Contributor I
edited April 17 in Help
Hi RapidMiner Community,

I need some help.

I am conducting an experiment for a paper I am writing. I want to compare a baseline experiment on Multi Target Prediction based on the following description.

"most straight-forward approach to solving MTP problems consists of constructing one model M for every target independently, and to concatenate the predictions of these models into the sought multi-target prediction. In the multi-label classification community, this model M for every target independently, and to concatenate the predictions of these models into the sought multi-target prediction."

I have put together operators to model 2 targets independently and all is working until to the point of the Multi Label Performance operator. I have set it to "auto detect label and prediction attributes", but it is not able to read the prediction attributes that I have set using the Set Roles operator before it. I have attached the workflow and the Set Role operator's parameters.

Anybody can suggest a workaround this? Would really appreciate it.

Regards






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  • ruhailaruhaila Member Posts: 3 Contributor I
    edited April 17
    Thanks.
    Your suggestion works.
    I am aware of the Multi Label Modeling, however, I am doing an experiment that can be described by the following,

    "most straight-forward approach to solving MTP problems consists of constructing one model M for every target independently, and to concatenate the predictions of these models into the sought multi-target prediction. In the multi-label classification community, this model M for every target independently, and to concatenate the predictions of these models into the sought multi-target prediction."

    That is to be my baseline.

    Additionally, is there a specific format for "confidence attributes"? Multi Label Performance is asking for this since my target variable is nominal. The error stated that the confidence attribute does not exist. I tried different possible formats,

    confidence(anxiety-severity-lvl = Moderate)
    confidence_anxiety-severity-lvl = Moderate
    anxiety-severity-lvl = Moderate

    but to no success.


  • ruhailaruhaila Member Posts: 3 Contributor I
    Found the answer in this online documentation.ย 

    https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/ensembles/multi_label_model_learner.html

    It would be good if Rapidminer could update this info in the Multi Label Performance operator's Help note.ย 

    Thank you and regards.ย 


  • tftemmetftemme Administrator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, RMResearcher, Member Posts: 160  RM Research
    Hi @ruhaila,

    Good to hear that it helped. I honestly don't see a difference between your experiment and the Multi Label Modeling operator. Cause you select the target variables in the operator and the operator will built one model M for every target independently. When you use the Multi Label Model in Apply Model, it will generate prediction and confidence attributes for each target variable and concatenate them.

    Yes you are right, the description of the expected confidence roles is not described in the Multi Label Performance operator, will see that we change this. The reason was, the operator were designed to be used together with the Multi Label Modeling operator (as I described above), so it was forgotten. Thanks for the feedback.

    Best regards,
    Fabian

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