Machine Learning Model for increase of revenue
Hi everybody,
for university I got a dataset of a telecommunication companie. I shall develop activities to increase the revenue.
I thought about churn prevention as first plan to increase revenue.
But for development of other activities I have some problems how to start.
I have a column MonthlyRevenue which is a float number and a column PercChangeRevenues which determines the change of revenue to the month before.
So I think I have to analyse which combination of attributes leads to a high value of revenue.
Which steps do I have to do after Data preparation (missing values and so on) ? Which operators can I use?
And is it better to group revenue into intervals?
For example revenue groups:
Group 1: 0-20€
Group 2: 21-40€
Group 3: >40€
Attached you can find my data.
Thanks for support 
Marc
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here is the Data File
I would recommend going through some of the basic tutorials in academy.rapidminer.com to learn how to set up your data and use RapidMiner. Then I would start by trying a simple linear regression on your monthly revenue variable (your label) with your other attributes.
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I would recommend going through some of the basic tutorials in academy.rapidminer.com to learn how to set up your data and use RapidMiner. Then I would start by trying a simple linear regression on your monthly revenue variable (your label) with your other attributes.