Frequently Asked Questions

What is the Difference Between Normalization and Standardization?

Both Normalization and Standardization are used for Feature Scaling. Below are the differences between them.



Data should follow a Normal Distribution. It is not required for data to follow a Normal Distribution.
The value lies from -x and +x. There is no boundary range. The mean and standard deviation of standardized data is 0 and 1 respectively. The value lies between 0 and 1 or -1 and +1.
Data can be standardized using methods like z-score. Data can be normalized using methods like MinMax Scaler.
Mean and Standard Deviation are used for Scaling. Minimum and Maximum values are used for Normalization.
Standardization is slightly affected by outliers. Normalization is slightly highly affected by outliers.

Z – Score Formula

A z-score tells you where the value lies on a normal distribution curve.

z-score = 

μ = mean
σ = standard deviation
x = current value

MinMaxScaler Formula

MinMaxScaler is a normalization method that uses the maximum and minimum values of a distribution to calculate the normalized value.

x = current value
xmin = minimum value of the distribution
xmax = maximum value of the distribution


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