针对不同重要性的样本，采用不同的惩罚因子进行逼近，在训练错误率和模型复杂度之间进行权衡。
Different penalty factors are assigned to the sample data of different importance, and the tradeoff can be determined between training errors and model complexity.
应用最佳一致逼近理论，从最小条件出发建立了评定平面度误差的数学模型，对评定平面度误差的理论问题进行了分析研究。
In this paper, the mathematical model of flatness error is established. The theory of optimal approximation is used to analyze the theoretical problem of flatness error.
跨越这一障碍的有效方法之一是采用参数矩阵的低秩逼近，目的是控制模型复杂度。
Low rank approximation to parametric matrix has recently been proven to be an effective method to control the complexity of models.
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