The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here
Time Series Forecasting for Data
Contributor II have a marine dataset with 3 attributes (Year, Species [categorical], Catch). I need to forecast the catch of each individual species(there are 8 species) for next 5 years. Is it possible with Windowing operator? Can someone please help me out with this? Thanks in advance
Tagged:
0
Answers
Of course it is possible :-), with RapidMiner it almost always is.
However, in these types of cases, you may find that you need to create 5 separate forecast models. Of course, if the data structure is the same for each, then you can easily reuse the same modeling setup and just loop through the setup by selecting only examples for each species separately for each run.
If you install the Time Series extension, there should be a new template available on the Studio startup page (or you can navigate there from your repository under Samples under Templates) which will help you get your first process set up. Take a look at the attached screenshot.
Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts
@Telcontar120 is right and if you want more info about how to window, read this thread: http://community.rapidminer.com/t5/RapidMiner-Studio/Time-Series-using-Windowing-operator-in-RapidMiner/m-p/31791
Thank you Brian T for you quick reply. I went through the above mentioned templete and the link provided by Thomas Ott. I understood the concept of windowing, but I could only forecast the values which are already present in my ExampleSet. I have data from 1980-2016. So with the windowing operator with parameters as window size = 5, step size = 1, horizon= 1, I could only get the forecasted value of 2016 which is already present in my dataset. I tried changing the forecast models(Linear regression, SVM etc) but the forecasted output dint change at all. I dont know wether I had gone wrong somewhere. What if I wanted to forecast value of 2017 using the previous 5 years data?
Take a look at the sample processes I posts here: http://community.rapidminer.com/t5/RapidMiner-Studio/Recall-Error/m-p/37302#U37302
This process was taking out of Vijay and Bala's book (Chp 10) and uses the existing time series to forecast into the future based on the model it created. It's really neat but you'll have to tweak it to your data set.