指出子空间信息准则是模型选择的一种新准则，它在一些假设条件下，给出推广误差的一种无偏估计。

Subspace information criterion is a new criterion for model selection, it gives an unbiased estimate for the generalization error under some assumptions.

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理论上给出了算法的流大小的无偏估计，相对误差的上界以及时间和空间复杂度。

Unbiased estimation of flow size, the upper bound of relative error and the time and space complexity are deduced theoretically.

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实验结果表明，该算法平均误差率较小，无偏性较好，在数据缺失较为严重的情况下也能完成填补。

Experimental results show that it has a small average error rate and good unbiasedness, it can still complete data under severe missing circumstance.

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