The paper proposes nine combined classifiers, including Partial Least Squares (PLS), Linear Discriminant Analysis (LDA), K-Nearest Neighbor(KNN) method, Decision Tree (DT), etc., which are used to analyze the serum proteome data sets of young transgenic tumor mice and normal control mice. It expounds the principle and method, and compares the classification accuracy of the combined classifiers.