COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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standardization
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normalization
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Either A or B
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None of the above
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Detailed explanation-1: -Normalization typically means rescales the values into a range of [0, 1]. Standardization typically means rescales data to have a mean of 0 and a standard deviation of 1 (unit variance).
Detailed explanation-2: -To normalize the vector, we divide each component by the magnitude of the vector in order to scale down to 1. For example, a vector with value 10 divided by 10 equals 1. To scale down to vector size 1, all other components need to be divided by the same amount, 10, as well.
Detailed explanation-3: -Standardization: Standardizing the features around the center and 0 with a standard deviation of 1 is important when we compare measurements that have different units. Variables that are measured at different scales do not contribute equally to the analysis and might end up creating a bais.
Detailed explanation-4: -part of Course 137 Signal Processing Techniques For a mean of 0 and a variance of 1, this is known as standardization or Z-score normalization.