The invention discloses a
data mining method with a model early-warning updating mechanism, and relates to the field of CRISP-DM (cross-
industry standard process for
data mining). The method includes:1, obtaining a preliminary scheme of a service objective by commercial understanding, and defining a model failure determination principle according to the service objective; 2, carrying out data understanding and
data preparation in sequence on the basis of the preliminary scheme to obtain a
data set suitable for modeling analysis; 3, training
multiple models on the basis of the
data set and thefailure determination principle to complete establishment and optimization of the models; 4, carrying out model evaluation and preliminary deployment on the multiple established models, then judgingwhether the same meet an early-warning rule and need to be updated, if the same meet the early-warning rule, recalculating the models to complete updating, and then
jumping to a step 5, and if the same do not need to be updated, directly
jumping to the step 5; and 5, carrying out final deployment of the models to
complete data mining. According to the method, problems of low precision and high costs brought by repeated execution processes caused by existing
data mining processes due to smaller model numbers are solved, and effects of improving model precision and reducing costs are achieved.