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Sales Predictions

PapadPapad Computer Science StudentMember Posts: 68  Guru
edited June 27 in Help
Hello everyone,
I am working on a dataset which contains sales of some products. The format is like:
           product1_sales |  product2_sales |  product3_sales | factor1 | factor2
Date | 
I want to predict future sales, and the only thing I have are the factors for future.
What do you suggest me? Do you think that a linear model is ok?
I also wanted to ask, how can I do this with auto model? I can predict only the data I already know, so have I got to 
add some empty queries to my dataset in order to predict them?


Secondly, in another dataset , I have this kind of format:
                   Speed | Pressure | Temperature
Timestamp|

This is about a kind of machines. I also have another dataset which gives alarms if an event happens in a specific timestamp.
So I want to find correlations at first, and then I want to built a model in order to understand every time if something will happen before I have an alarm, in order not to stop the machine. Generally I want my model to recognize the flow of my data and predict what is gonna happen. 
To sum up, how can I say to my model for example that if speed is under 10 and pressure over 5 I want you to recognize it as a problem of a kind?
Thanks in advance.

Best Answer

Answers

  • Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,277   Unicorn
    You should take a look at the time series operators and their associated tutorials.  There are a lot of different approaches you could take to this type of data, but the time series operators are going to be your best starting point.
    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
    sgenzerPapad
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