APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
The technique Which is used to re-scales features with a distribution value between 0 and 1
|
|
Normalization
|
|
|
standization
|
|
|
none of the above
|
|
|
both a& b
|
Explanation:
Detailed explanation-1: -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.
Detailed explanation-2: -Standardization: It is a very effective technique which re-scales a feature value so that it has distribution with 0 mean value and variance equals to 1.
Detailed explanation-3: -To normalize the values in a dataset to be between 0 and 1, you can use the following formula: zi = (xi – min(x)) / (max(x) – min(x)) where: For example, suppose we have the following dataset: The minimum value in the dataset is 13 and the maximum value is 71. More items •26-Apr-2021
There is 1 question to complete.