INFORMATION NETWORK FRAMEWORK FOR FEATURE SELECTION FIELD

摘要

Systems and methods are disclosed to facilitate real time feature selection. Some embodiments of the invention describe a framework for feature selection via an iterative probabilistic graph learning approach. A feature dataset can be collected and transformed into an information network in a star schema layout, respecting feature type differences. Features can then be simultaneously ranked in the network, both with respect to feature types and the central feature. Feature selection is then performed, allowing for both the identification of valuable features, and, if dealing with labeled data, the ability to construct predictive rules for future data records based on the ranked and selected feature set.