Data mining was introduced and 178 sets of alternating current (AC) corrosion data were collected from published data and our research group. The AC current density (J AC ), direct current (DC), current density (J DC ), the ratio of AC/DC current density (J AC /J DC ), and cathodic protection potential (IR-free potential, E IR-free ) were defined as the input feature and the priority of feature subset was ranked as (J AC , J DC ) > (J DC , J AC /J DC ) > (J AC , E IR-free ) >J AC > (J AC / J DC , E IR-free ) > J AC /J DC . Then, based on the different feature subsets, the AC corrosion rate model was established by the random forest algorithm, and the generalization ability of the model was verified on the test data respectively.Finally, the mapping relationship between AC, DC parameters, and corrosion rates was presented and the limiting values of (J AC , J DC ) and (J DC , J AC /J DC ) were given.