ROBUST FEATURES GENERATION ARCHITECTURE FOR FRAUD MODELING

摘要

Methods and systems for generating robust computer models for detecting fraudulent electronic transactions are presented herein. A set of dominative features is selected from candidate features using multiple feature selection algorithms, where each dominative feature in the set of dominative features is dominative over every remaining candidate feature. The multiple feature selection algorithms may include at least one univariate feature selection algorithm and at least one multivariate feature selection algorithm. The set of dominative features may be reduced to a number of representations, where each representation represents an aspect of the set of dominative features. The representations may then be used to generate the robust computer model.