Due to the reason that the randomness of the parameters in the MASK algorithm always leads to the volatilityand uncertainty of the mining results, this paper proposed an optimization algorithm for the maximum likelihood estimationof the parameters to choose a parameter that is most approximate to the common parameters from the parametergroup that has been generated randomly. Such a parameter generated as above represented all of the parameters in the parametergroup. The simulation experiment proves that the application of such a parameter has reduced the great volatilityhidden in the mining results to some extent.
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