Is there a way I can run different predictive models in parallel on the same dataset to find which is the most accurate? I don't seem to be able to split connections two ways.
You may also be interested in the "Compare ROCs" operator, which allows you to run mulitple learner types inside and then see how they compare in terms of ROC on your data. These aren't optimized learners but they will give you a general sense of which types of algorithms look to be better suited to your specific problem.
Brian T. Lindon Ventures Data Science Consulting from Certified RapidMiner Experts
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MartinLiebigAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts: 3,507 RM Data Scientist
You can also combine a optimize with a Select Subprocess operator to always get the better model.
~Martin
- Sr. Director Data Solutions, Altair RapidMiner - Dortmund, Germany
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You an use a Multiply operator to split your training data and from there connect differnet algorithms and have multiple outputs.
You may also be interested in the "Compare ROCs" operator, which allows you to run mulitple learner types inside and then see how they compare in terms of ROC on your data. These aren't optimized learners but they will give you a general sense of which types of algorithms look to be better suited to your specific problem.
Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts
You can also combine a optimize with a Select Subprocess operator to always get the better model.
~Martin
Dortmund, Germany