This technique consists of subtracting the mean of the column from each value in a column, and then dividing the result by the standard deviation of the column. The formula to achieve this is the following:
The result of standardization is that the features will be rescaled so that they’ll have the properties of a standard normal distribution, as follows:
- μ=0
- σ=1
μ is the mean and σ is the standard deviation from the mean.
In summary, the z score (also called the standard score) represents the number of standard deviations with which the value of an observation point or data differ than the mean value of what is observed ...
