MSE:均方误差
均方误差是英文“Mean Squared Error”的缩写形式MSE,这一简写方式在书写和使用过程中更为高效便捷。该术语在统计学和机器学习领域应用广泛,尤其在美国政府机构的相关报告和数据分析中频繁出现。其核心含义是通过计算预测值与真实值之间差异的平方的平均数,来衡量模型的预测精度。
Mean Squared Error具体释义
Mean Squared Error的英文发音
例句
- The final result of the model was the addition of the two model's validation values, and the root mean squared error of prediction ( RMSEP ) was used to estimate the mixed model.
- 最终预测结果为两个模型预测值之和,以模型的预测标准偏差(RMSEP)作为评价指标,以便考察新方法的有效性。
- A mathematical model is first established for the cooperative precoding matrix optimization which is based on the minimization of the mean squared error.
- 首先基于系统均方误差(MSE)函数最小化准则建立了数学模型;
- We demonstrate through simulations with images contaminated that the performance of the proposed method surpass that of previously published method both visually and in terms of mean squared error.
- 实验结果表明,与现有的图像去噪方法相比,本文方法无论是在视觉还是在均方误差(MSE)等方面均有更好的效果。
- Mean squared error criterion;
- 文中采用了二种算法:(1)均方误差(MSE)准则;
- Thus we propose two serial iterative linear minimum mean squared error ( LMMSE ) estimation detection methods.
- 为此,本文提出了两种基于串行迭代的线性最小均方误差(MSE)(LMMSE)估计的检测方法。
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