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By Prof. Fazal Rehman Shamil
Last modified on July 20th, 2020

Min Max is a data normalization technique like Z score, decimal scaling, and normalization with standard deviation. It helps to normalize the data. It will scale the data between 0 and 1. This normalization helps us to understand the data easily.

For example, if I say you to tell me the difference between 200 and 1000 then it’s a little bit confusing as compared to when I ask you to tell me the difference between 0.2 and 1.

Min Max normalization formula

marks

8
10
15
20

Min:

The minimum value of the given attribute. Here Min is 8

Max:

The maximum value of the given attribute. Here Max is 20

V: V is the respective value of the attribute. For example here V1=8, V2=10, V3=15, and V4=20

newMax:

1

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newMin:

0

marks

marks after Min-Max normalization

80
100.16
150.58
201

Min max normalization example

Comparison of Min-Max Normalization and Z-Score Normalization

Let’s see the comparison of Min-Max Normalization and Z-Score Normalization

Min-max normalizationZ-score normalization
Not very well efficient in handling the outliersHandles the outliers in a good way.
Min-max Guarantees that all the features will have the exact same scale.Helpful in the normalization of the data but not with the exact same scale.

Implementation of Min-Max normalization in C++

  • Calculate and show the maximum value from the array.
  • Calculate and show the minimum value from the array.
  • Calculate and show the average value from the array, and the number of values that are larger than the average.
  • Calculate and show the normalized values of the original array values.

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