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: -What is Standardization? Standardization is another scaling method where the values are centered around mean with a unit standard deviation. It means if we will calculate mean and standard deviation of standard scores it will be 0 and 1 respectively.
Detailed explanation-2: -The two most discussed scaling methods are Normalization and Standardization. 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-3: -1)Min-Max scaler This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g., between zero and one. This Scaler shrinks the data within the range of-1 to 1 if there are negative values.
Detailed explanation-4: -Standardization is an operation that transforms a batch of input data to have a mean of zero and a standard deviation of one. Within the BN algorithm, we need to calculate the mean of the mini-batch and then the variance.