Data Preprocessing Technique: Min-Max Scaling

Scaling the feature vectors is a different data preparation method. The values of each feature can range between a wide range of random values, necessitating the scaling of feature vectors. To put it another way, scaling is crucial since we don’t want any feature to be artificially large or small. Our input data, or feature vector, can be scaled with the help of the Python code below:

The output to the above code will show as follows: