The present invention discloses a hierarchy gravity model based imbalanced data classification method and a system therefor. The method comprises the following steps: S1, acquiring a to-be-classified sample set Z, wherein each sample in the to-be-classified sample set Z comprises D attributes, and D is a positive integer; S2, performing interval division on attribute values of samples, dividing each attribute into L intervals, dividing the samples into LD D-dimensional cubes, and calculating an attribute weight, wherein L is a positive integer; and S3, dividing feature space, placing the to-be-classified sample set Z into a corresponding hierarchy D-dimensional cube, and performing label classification on the samples in conjunction with a gravity model. The hierarchy gravity model based imbalanced data classification method and the system therefor have the following advantages: the attributes are weighted at different resolutions for a multi-hierarchy model, and classification performance of a hierarchy model is improved; classification efficiency is improved by dividing the attributes at different resolutions and establishing a hierarchy classification model; and classification precision of data in a space overlapping area is optimized by using a partial gravity model.