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What type of model to use
Contributor II
Backstory: I just started using RapidMiner and I'm working with a system where a node will get pinged randomly throughout the day. From this I'm given a timestamp and I've also managed to split that timestamp up to give me month, day, hour, day of the week, and frequency per hour (not really sure if any of these features are actually significant). I'm trying to use RapidMiner to predict when a node goes 'missing'.
I want RapidMiner to take in all of this info and then spit out how confident it is that a node is missing/not missing based on how long it's been since the last ping vs. the frequency that the node has gotten in similar situations (ex. same day of week, same hour in previous days, etc). I'd be very thankful if anyone could point out some viable data models for me. If it changes anything, I also have a pretty large amount of data (been running my app for over 3 months).
I want RapidMiner to take in all of this info and then spit out how confident it is that a node is missing/not missing based on how long it's been since the last ping vs. the frequency that the node has gotten in similar situations (ex. same day of week, same hour in previous days, etc). I'd be very thankful if anyone could point out some viable data models for me. If it changes anything, I also have a pretty large amount of data (been running my app for over 3 months).
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