RMSE root mean square error learning notes

1. root mean square error,It is the square root of the ratio of the sum of squares of observed values to the true value of observed number N,In actual measurement, the number of observations N is always limited, and the true value can only be replaced by the most trustable (optimal) value. the Gini error is very sensitive to the extremely large or extremely small error in a group of measurements. Therefore,Root mean square error can reflect the precision of measurement.Root-mean-square error. When a certain amount is measured for many times, the root-mean-square deviation of the true error in the measurement column is obtained (the arithmetic mean value of the square of the true error is then obtained), which is called a standard deviation, expressed as σ. σ reflects the degree to which the measurement data deviates from the actual value. The smaller the value, the higher the measurement accuracy. Therefore, σ can be used as the standard to evaluate the accuracy of this measurement process.

2.The root-mean-square value (RMS) is also called an effective value.The calculation method is square first, then average, and then square.

3. Standard Deviation)The standard deviation is the arithmetic square root of the variance, also known as mean square error. It is the mean of the distance from the mean of each data, and it is the deviation of the mean squared and the mean after the mean, represented by σ, standard deviation Can reflect the degree of discretization of a dataset.

RMSE root mean square error learning notes