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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Noise removal
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Normalization
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Data encoding
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Detailed explanation-1: -Data normalization is a technique used in data mining to transform the values of a dataset into a common scale. This is important because many machine learning algorithms are sensitive to the scale of the input features and can produce better results when the data is normalized.
Detailed explanation-2: -The most common techniques of feature scaling are Normalization and Standardization. Normalization is used when we want to bound our values between two numbers, typically, between [0, 1] or [-1, 1]. While Standardization transforms the data to have zero mean and a variance of 1, they make our data unitless.
Detailed explanation-3: -in scaling, you’re changing the range of your data, while. in normalization, you’re changing the shape of the distribution of your data.