Error Evaluation: RMS value + root mean square error (RMSE) + standard deviation (Deviation)

1, RMS, also known as the validity , it is calculated by first square, then average, and then the root.

2. RMS error, which is the square root of the squared and observed n ratios of the observed and true values, and in the actual measurement, the number of observations n is always limited, True values can only be replaced with the most trustworthy (best) value. The square root error is very sensitive to the large or small errors in a set of measurements, so the RMS error can well reflect the precision of the measurement. The RMS error, when measured in a certain amount, takes the RMS difference of true error of the measurement column (the arithmetic mean of true error squared again), called the standard deviation, expressed in σ. Σ reflects the degree to which the measured data deviates from the true value, the smaller the σ, the higher the accuracy of the measurement, so σ is used as a criterion for measuring the accuracy of this measurement process.

3, Standard deviation (standarddeviation), the standard deviation is the arithmetic square root of the variance, also known as the mean variance (mean square error), is the average distance from the average deviation of the data, it is the square and average of the mean squared, with σ, the standard deviation can reflect the degree of dispersion of a data set .