11-28-2016 04:09 PM
11-29-2016 01:47 AM
welcome to the community!
It is technically possible to take the equation from RM and put it into RM. But the big question is - why do you want this?
A Model is always the connection of the preprocessing and the machine learning part itself. If you use a machine learning model on a table which is not prepeared in the very same way it will work but create wrong or unreasonable results.
Why dont you create a rm porcess: Read Excel -> Prepare Data -> Apply Model -> Write Excel
11-29-2016 02:37 AM
11-29-2016 09:27 AM
IMHO, the method that Martin proposes is probably the faster and better solution.
Import your data (by Excel or Database) do your training and scoring in RapidMiner, and at the end write out the predicted results to Excel. Going through the trouble of finding the weights in RapidMiner to then plug it into a Excel Logistic Regression model and crunching it there feels very time consuming.
However, you can extract the Logistic Regression operator weights by using a Weight to Data operator and then Write Excel.
11-29-2016 04:27 PM