Timeweaver: A genetic algorithm for identifying predictive patterns in sequences of events

  • Weiss G
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Abstract

Learning to predict future events from sequencesof past events is an important, real-world,problem that arises in many contexts. This paperdescribes Timeweaver, a genetic-based machinelearning system that solves the event predictionproblem by identifying predictive temporal andsequential patterns within data. Timeweaver isapplied to the task of learning to predicttelecommunication equipment failures from250,000 alarm messages and is shown tooutperform existing methods.1 INTRODUCTIONData is being generated and stored at an ever-increasingpace, and, partly as a consequence of this, there has beenincreased interest in how machine learning and statisticaltechniques can be employed to extract useful knowledgefrom this data. When this data is time-series data, it isoften important to be able to predict future behavior basedon past data. In this paper we are interested in the problemof predicting specific types of rare future events, whichwe refer to as target ...

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Authors

  • G.M. M Weiss

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