Value Selection Widget with Gradient Boosted Tree Learner

Hi everybody
you might now the dataset in-vehicle-coupon reccomendation.
In-Vehicle Coupon Recommendation - UCI Machine Learning Repository

I would like to create a machine learning model where you can choose parameters (variables) of different columns to get a forecast whether the coupon (with the chosen variables) will be accepted or not (prediction probability)

for the variable input I would use the node “Value Selection Widget”.
Variables would be destination, weather, passanger, gender, age, materialstatus, children, income, material status, income, education, occupation, income, coupon, bar, coffehouse, carryaway, restaurant<20, restaurant 20-50, tocoupon_geq15min, tocoupon_geq25min.

I already set up a workflow but i don’t know where to put the value selection widget exactly and how to configure the ML Learner and predictor to get a result based on my variables.

Maybe you could help me to complete the workflow or give me a better way so solve this question.

Thank you very much in advance!

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Hello @bibi_bianca,

For doing so you’ll have to refer to this documentation :

Here is a sample of how to start:

You have to ways to do it. I let you check that !


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