SVM model optimal multi-parameter selection method for imbalanced data recognition was proposed. First, the connotation and necessity of SVM model multi-parameter selection were theoretically analyzed. Then, a multi-parameter selection criterion based on F-measure was given, which can represent the recognition performance completely. The genetic algorithm was used in search of optimization of multi-parameter in parallel parameter optimal selection. The proposed method can get the global optimal solutions of SVM model multi-parameter, and avoid the local optimal solution caused by gradient method, and can also decrease the computational complexity of experiential selection method. The experimental results of the benchmarks and radar HRRP data sets reveal that the proposed multi-parameter selecting method can get the global optimal solution of SVM model. The recognition performance of the optimal SVM model can achieve much improvement.