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Edit Auto Model process to insert 'vote' operator

Hi,

i have used 'Titanic' data example with Auto Model to predict the survived passengers using Naive Bayes and generate a process which i attach here.

My question is, taking as reference the documentation:

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

What should I modify exactly in the process I attached to make it work correctly? Can someone give any illustrative example? I would be very grateful.

Thanks very much

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Accepted answers

varunm1

It should work, maybe the run time data that we are logging is changing due to our manual modifications, you can disable that operator if you are ok with not having run times recorded.

All comments

varunm1

Hello @User222697

To use "vote" operator you need at least two base learners, you cannot use with a one learning algorithm. In the below screenshot, I used your process and made modifications during model training. You can see the left part is where I used to multiply and vote during training and then the right part is where I show the two base learners I used inside vote operator.

Image: https://us.v-cdn.net/6030995/uploads/editor/5f/ezcvycsof04q.jpg

Is this what you are looking for? If not, provide us more details so that we can help you with the solution.

User222697

Hi,

i have tried to do this but shows an unexpected error, see attached screenshot, it is required to implement another changes into the process to work properly?

Thanks

Image: https://us.v-cdn.net/6030995/uploads/editor/oe/o9fg5c4wqpit.png

varunm1

Can you try running the XML from below attached file and inform if it is throwing an error?, It is working fine for me.

titanicautomodelprocess.txt

User222697

Hi,

your model works fine, however, if i try to apply in another processes created by Auto Model, it dont work .. is very strange

varunm1

It should work, maybe the run time data that we are logging is changing due to our manual modifications, you can disable that operator if you are ok with not having run times recorded.