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What is the best classification model to use?
Historical event data is available for each device. The number of different events is N. It is
necessary to predict the type of event that will happen in the future.
What is the best classification model for such a task?
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If by model you mean the method that is best applied to solve your problem, then the answer depends on what kind of data you have. Whether they depend explicitly or implicitly on time - if so, then you need to build process models based on time series and use appropriate prediction methods (which one can only be understood by analyzing the data).
If the data does not depend on time - then classification methods are used, and which one - any answer without a preliminary analysis of the data will be a guess, with an appropriate level of utility. Precisely because the method depends on data and a great many of them have been invented.
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