Optimizing Hidden Markov Model for Failure Prediction– Comparison of Gaine’s optimization and Minimum message length Estimator
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 2
Abstract
Computer systems are prone to failures. Failures are caused by faults that occur in a system. As faults are unknown and cannot be measured, they produce error messages on their detection. The approach presented here is to create a Hidden Markov Model from the given data of error sequence and describes two techniques, Gaines algorithm and Minimum message length estimator to obtain a most appropriate Hidden Markov Model with optimized number of states. For a given sequence it is shown that both the two techniques ensure same optimal Hidden Markov Model with maximum probability
Authors and Affiliations
N. Muthumani , Dr. Antony Selvadass Thanamani
Keywords
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