Regression with Random Forest ?
嗨RapidMiner,
I'm doing regression with 480 input features. I tried to use Deep Learning operator but the training Root Mean Square Error is still quite high. Now I'm trying to use Random Forest because of its Random Subspace approach, but found that the Random Forest operator cannot handle numerical label. How can I deal with this?
Thank you very much for your support.
Best Regards,
phivu
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earmijo MemberPosts:270Unicorn
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earmijo MemberPosts:270Unicorn
Install the R Script Extension. Verify you have R installed in your computer and run the code below. I adapted the code that comes with the application to run Random Forest for a regression problem.
<宏/ >Fetch example data Split the data in a training and a test set Train a RandomForest model in R and return it as an R object Apply the trained model on the test data 2
Answers
Thank you Earmijo, could you elaborate more on how to use RapidMiner with R to do regression with Random Forest?
That's great, thanks!
UPDATE: As of version 8.0, Decision TreeandRandom Forestcan now handle numerical labels and solve regression problems.
https://docs.www.turtlecreekpls.com/latest/studio/releases/changes-8.0.0.html?_ga=2.83072976.793993492.1515416834-774805979.1445867999