Learning geofence models directly

Abstract

Methods and apparatus are directed to geofencing applications that utilize machine learning. A computing device can receive a plurality of geofence-status indications, where a geofence-status indication includes training data associated with a geofence at a first location. The geofence is associated with a geographical area. The computing device trains a geofence-status classifier to determine a geofence status by providing the training data as input to the geofence-status classifier. The training data includes data for a plurality of training features. After the geofence-status classifier is trained, the computing device receives query data associated with a second location. The query data includes data for a plurality of query features. The query features include a query feature that corresponds to a training feature. The query data is input to the geofence-status classifier. After providing the query data, the trained geofence-status classifier indicates the geofence status.