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Good! The problem is that I do not find any detailed examples in the literature on using the 'Change and Deviation detection', compared to the broad coverage on other main 'Data mining' aspects.
I just want to try some examples to get familiar with it. Could you probably tell me some examples on how I can detect deviations compared to the previosly measured or normative values?
I just want to try some examples to get familiar with it. Could you probably tell me some examples on how I can detect deviations compared to the previosly measured or normative values?
A good starting point to learn more about change detection and the related topic of concept drift are the following Wikipedia entries:
http://en.wikipedia.org/wiki/Change_detection
http://en.wikipedia.org/wiki/Concept_drift
Im my publications on concept, you will also find further explanations and references:
http://www-ai.cs.uni-dortmund.de/PERSONAL/klinkenberg.html
Best regards,
Ralf
http://en.wikipedia.org/wiki/Change_detection
http://en.wikipedia.org/wiki/Concept_drift
Im my publications on concept, you will also find further explanations and references:
http://www-ai.cs.uni-dortmund.de/PERSONAL/klinkenberg.html
Best regards,
Ralf
In other words, can I assume that 'Change and Deviation' is an area which has to be newly exploted by the Rapidminer community, and there are no operators in the Rapidminer that are related to the 'Change and Deviation'?
If my conclusion is wrong, please give me the list of some important operators which can be used for it.
If my conclusion is wrong, please give me the list of some important operators which can be used for it.
RapidMiner supports 'Change and Deviation detection'. What details are you interested in? RapidMiner does not have a monolothic ChangeAndDeviationDetectionOperator. Every RapidMiner process is made up of several Operators that you combine to suit your needs. Also, you are asking a very broad question here. Where should I start?
If you have specific questions, I will be happy to answer them.
Best,
Simon