normalized root mean square error 文心快码BaiduComate 1. 解释什么是均方根误差(RMSE) 均方根误差(Root Mean Square Error, RMSE)是衡量观测值与真实值之间差异的一种常用指标,特别是在回归任务中。它通过对误差的平方取平均后再开方得到,可以有效避免误差正负相抵的情况,从而更加准确地反映模型的预测精度。RMSE的...
Normalized RMSE(Root Mean Square Error)是一种常用的模型评估指标,通常用于评估模型的预测精度。它是RMSE的标准化版本,可以将不同数据集的RMSE值进行比较。 Normalized RMSE的计算方法如下: NRMSE = \frac{RMSE}{y{\max} - y{\min}} 其中,RMSE是均方根误差,y{\max}和y{\min}分别是真实值的最大值和最...
简介:Normalized RMSE(Root Mean Square Error)是一种常用的用于评估预测模型的指标,它是在 RMSE 的基础上进行了归一化处理,使得不同数据集之间的 RMSE 可以进行比较。 Normalized RMSE(Root Mean Square Error)是一种常用的用于评估预测模型的指标,它是在 RMSE 的基础上进行了归一化处理,使得不同数据集之间的 RMS...
The normalized root mean square error in Fig. 3.Jian, FuXinhua, HuAstrid, VelroyenMartin, BechMing, JiangFranz, Pfeiffer
This paper proposes a new work load balancing measure based on the square errors that can be used in the case of identical parallel machines. Square error measures have been used for many problems, for example in variance determination, regression analysis, forecast errors, and design of experimen...
Finally, the coefficient of determination (R2) and Root Mean Square Error (RMSE) between the modeled NSTLR and the observed NSTLR were calculated to evaluate the accuracy of the modeled NSTLR. The mean values of R2 between DEM and NLST were improved 0.3, 0.42 and 0.35, rather than between...
Root mean square deviation Bond lengths (Å) 0.002 Bond angles (degrees) 0.51 Ramachandran plot Favored (%) 97.24 Allowed (%) 2.76 Outliers (%) 0.00 Average B-factor 32.63 Macromolecules 31.98 Ligands 72.83 Solvent 37.79 Author contributions H. T. and G. D. conceptualization; H. T. and...
7, reduced major axis (RMA) regression coefficients, the number of 30 m pixel values considered (n), the OLS regression coefficient of determination (r2), the OLS regression F-test p-value, the mean difference [2], the mean relative difference [4], and the root mean square deviation [3...
Normalized Root Mean Square Error Normalized Sample Covariance Matrix Normalized Sample Covariance Matrix Estimate Normalized Segmental Ejection Fraction Normalized Sgml Normalized Sgml Library Normalized Signal-To-Interference Ratio Normalized Signal-To-Interference Ratio Threshold Normalized Signal-to-Noise Ratio ...
6) root-mean-square error 均方根误差 1. The root-mean-square error of this method is less than 0. 所提出的基于粒子滤波的声源定位方法,在高斯噪声情况下,甚至在低信噪比(SNR<-20dB)情况下,定位的均方根误差RMSE值均小于0。 2. It was found from the comparison chart of the predicted dosage...