1. A computer-implemented method for determining an attribute for an online user of a candidate computing device, the method implemented using a host computing device, the method comprising: identifying, by the host computing device, a first set of model data including a first set of device data from a plurality of model computing devices, the first set of device data including location data and access data for the plurality of model computing devices; identifying a plurality of categories for an attribute of a population segment, each category defining a segment of the attribute, the population segment including the candidate computing device; training a classification model by the host computing device using the first set of model data and the plurality of categories; receiving a device identifier from the candidate computing device, the device identifier including device data of the candidate computing device; applying the device data of the candidate computing device to the classification model to generate an offline prediction of a category of the plurality of categories for the candidate computing device; determining a location of the candidate computing device using an IP address of the candidate computing device; generating an online prediction of a category of the plurality of categories for the candidate computing device using the location; and generating a composite prediction of a category of the plurality of categories for the candidate computing device by combining the offline prediction and the online prediction.
2. The method of claim 1 , further comprising: receiving, at the host computing device from the candidate computing device, a request for content; selecting, by the host computing device, a content item based on the composite prediction; and serving the content item to the candidate computing device in response to the request.