Meta Platforms, Inc.
Deep feature generation for classification

Abstract:

In one embodiment, a method includes a device configured to obtain a plurality of sparse, categorical, and numerical features. The device may generate a plurality of ordered combinations of features, wherein each ordered combination of features comprises at least a first feature and a second feature. The device may identify a user account of a social networking system and generate one or more deep feature values associated with the user account for each of the plurality of ordered combination of features. The generation may comprise extracting a first feature value and a second feature value associated with the user account using a social graph of the social networking system. The first and second feature values correspond to the first and second features of the ordered combination of features, respectively. The device may then train a machine-learning model using the generated deep feature values associated with the user account.