How can I evaluate my Auto Model for predicting future failures of vehicles/ components?
Hello Rapid Miner Community,
I am very new to data mining and rapid miner in general. What I learned is, that a model can be evaluated by dividing the data set into a training data set and an evaluation data set, e.g. 90/10. How do I implement an evaluation in the Auto Modeller? I have already looked in the community for entries on this topic, but found nothing suitable.
To my dataset:
I have a data set of 35k vehicles of which 1.5k vehicles have already failed due to a defect in a component. In my analysis I only look at one component at a time. My data consists of the respective IDs of the vehicles, mileage, production date, first registration date, repair date and various components of a vehicle such as engine, transmission, brake, weight variant, etc. In addition I analyze the components of the vehicles, because I have an indication of a mileage from only 14k vehicles out of these 35k. In total I have 22 columns.
I would like to create a time series analysis, with which I can drop out the vehicles in 3 or 6 months or up to 200k km, for example.
My following steps would be a time series analysis with Arima to create. But first I want to understand and evaluate the results of the Auto Modeler.