Hi, we don't have an explicit ARIMA operator in rapid miner, but I think you could get the same if you apply a MovingAverage operator at first, then window the data and apply a linear regression on the windowed data.
你必须看在预处理/系列组织p. Take a deeper look on all operator descriptions there.
Hi, I followed the method you mentioned above.I used WindowExamples2ModelingData operator.But i am not getting the idea about label-name-stem. Thanks Ratheesan
Hi, the label name stem is actually only the name of the label attribute before windowing. After windowing you should have something like label-0, label-1, label-2 and so on, denoting the value of the label in the indexed time points. The stem then would be "label".
Whenever I am working with WindowExamples2ModelingData operator I am getting "NumberFormatException caught for Input String" message. Any suggestion regarding this?
Hi, here's a small example process. I hope this will guide you around the pitfalls in this area. If you add a few breakpoints, you will see, what each operator does.
Maven
Answers
we don't have an explicit ARIMA operator in rapid miner, but I think you could get the same if you apply a MovingAverage operator at first, then window the data and apply a linear regression on the windowed data.
你必须看在预处理/系列组织p. Take a deeper look on all operator descriptions there.
Greetings,
Sebastian
I followed the method you mentioned above.I used WindowExamples2ModelingData operator.But i am not getting the idea about label-name-stem.
Thanks
Ratheesan
the label name stem is actually only the name of the label attribute before windowing. After windowing you should have something like label-0, label-1, label-2 and so on, denoting the value of the label in the indexed time points. The stem then would be "label".
Greetings,
Sebastian
Whenever I am working with WindowExamples2ModelingData operator I am getting "NumberFormatException caught for Input String" message. Any suggestion regarding this?
Thanks,
Ratheesan
here's a small example process. I hope this will guide you around the pitfalls in this area. If you add a few breakpoints, you will see, what each operator does.Greetings,
Sebastian