Like a Sigmoid transformation, a Z-Score transformation provides rescaling of continuous numeric data in a more sophisticated way than a Rescaling transformation. In a Z-Score transformation, a numeric column is transformed into its Z-score based on the mean value and standard deviation of the data in the column. It transforms each column value into the number of standard deviations from the mean value of the column. This non-linear transformation is generally more useful in data mining than a linear Rescaling transformation.
For a value, the number of standard deviations away from the mean is calculated as: