Standardization

What is Standardization?

Standardization is another scaling technique where the values are centered around the mean with a unit
standard deviation. This means that the mean of the attribute becomes zero and the resultant
distribution has a unit standard deviation.

Here’s the formula for standardization:

μ is the mean of the feature values and

σ is the standard deviation of the feature values.

Note that in this case, the values are not restricted to a particular range

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Standard Deviation And Variance

Standard Deviation : Standard deviation is a number that describes how spread out the values are. A low standard deviation means that most of the numbers are close to the mean (average) value. A high standard deviation means that the values are spread out over a wider range. Example: This time we have registered the speed of 7 cars: speed = [ 86 , 87 , 88 , 86 , 87 , 85 , 86 ] The standard deviation is: 0.9 Meaning that most of the values are within the range of 0.9 from the mean value, which is 86.4. Let us do the same with a selection of numbers with a wider range: speed = [ 32 , 111 , 138 , 28 , 59 , 77 , 97 ] The standard deviation is: 37.85 Meaning that most of the values are within the range of 37.85 from the mean value, which is 77.4. As you can see, a higher standard deviation indicates that the values are spread out over a wider range. The NumPy module has a method to calculate the standard deviation: import numpy speed = [ 86 , 87 , 8...

Normalization

What is Normalization? Normalization is a scaling technique in which values are shifted and rescaled so that they end up ranging between 0 and 1. It is also known as Min-Max scaling. Here’s the formula for normalization: Here, Xmax and Xmin are the maximum and the minimum values of the feature respectively. When the value of X is the minimum value in the column, the numerator will be 0, and hence X’ is 0. On the other hand, when the value of X is the maximum value in the column, the numerator is equal to the denominator and thus the value of X’ is 1 If the value of X is between the minimum and the maximum value, then the value of X’ is between 0 and 1

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