A method and a system for data imputation and classification are provided. The system includes a database, a historical sample imputation module and a current sample imputation and classification module. In the method, at first, an imputation calculation is performed on each of classified historical sample groups to obtain a basis matrix and a missing value corresponding to each of the classified historical sample groups. Thereafter, a sample classification stage is performed. In the sample classification stage, an IPP (Iterative Projection Pursuit) algorithm and an equation of nonlinear inequality constraints to calculate weighting vectors corresponding to a current sample. Thereafter, plural candidate samples corresponding to different classes are calculated in accordance with the basis matrix and the weighting vectors, and the sample class of the current sample and a prediction value for a missing value of the current sample are determined accordingly.
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