A method for managing a context classification, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; and selecting a configuration parameter from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input; and causing a classifier to perform the context classification according to the granularity input, indicating the granularity level of the context classification output, in response to the request by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification; wherein a configuration parameter for a granularity input indicating a higher granularity level is associated with a higher resource usage level and a configuration parameter for a granularity input indicating a lower granularity level is associated with a lower resource usage level. receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; and selecting a configuration parameter from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input; and causing a classifier to perform the context classification according to the granularity input, indicating the granularity level of the context classification output, in response to the request by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification; wherein a configuration parameter for a granularity input indicating a higher granularity level is associated with a higher resource usage level and a configuration parameter for a granularity input indicating a lower granularity level is associated with a lower resource usage level. <EOS>