Recently reference to a blog , feel better put this concept, I passed the same tidy blog here:
- Mean variance relationship is the mean of the data sequence, the mean square error is the relationship between the data sequence and the true value; wherein the relationship between the mean focus and the true value;
- Variance is the square of the data between the mean (mathematical expectation) and;
- The standard deviation is the average of variance of square root, square root;
- The standard deviation is all variance, standard deviation is the standard deviation;
- Mean square error and the mean square of the distance from the true values for each data, i.e., the average square error and, close to the calculated variance of the form, its square root is called the root mean square error, root mean square error and the standard was poor form close;
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