Abstract:Most information and communication technologies systems providing some form of intelligence to future smart cities will more or less use data-based predictive models. Since the amount of data collected increases rapidly, it is becoming crucial to select proper data that are relevant and useful for the specific predictive model. The importance and usefulness of two wrapper feature selection methods is demonstrated here on 23 time series appearing typically in smart city area. Particularly, high dimensionality r… Show more
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