This technique consists of subtracting the mean of the column to each value in a column, and then dividing the result for 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
where 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 is greater than the mean value of what ...
