Learning to predict rare events in event sequences

摘要: Learning to predict rare events from sequences of with categorical features is an important, real-world, problem that existing statistical and machine learning methods are not well suited solve. This paper describes timeweaver, a genetic algorithm based system predicts by identifying predictive temporal sequential patterns. Timeweaver applied the task predicting telecommunication equipment failures 110,000 alarm messages shown outperform methods.