In general, interferometers are used to perform electron density measurements in magnetically confined plasma, where the electron density is dependent on the refractive index of the plasma. Measurements can be made through comparisons of the phase shift variation between the probe and reference laser beam. The plasma electron density should vary continuously during discharge; however, the fringe jump is a step-like change of the apparent electron density caused by a sudden jump of the measured phase shift. The appearance of fringe jump will degrade the interferometric measurements accuracy. This study attempted to solve the fringe jump problem on the polarimeter-interferometer (POINT) diagnostics system of the Experiment Advanced Superconducting Tokamak (EAST) by proposing a support vector machine model for electron density fringe jump detection and correction. The established model can efficiently classify the fringe jump data from the raw measurement data in a manner robust to noise and interference, and subsequently correct the jump. This model greatly improves the correction efficiency and precision of electron density data from the POINT system, and is expected to be embedded into the plasma control system to perform more accurate real-time electron density feedback control. Moreover, the algorithm is not limited to specific fusion devices or interferometer diagnostics, and is applicable to other interferometric measurement systems.