Python Machine Learning Cookbook(Second Edition)
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Standardization is particularly useful when we do not know the minimum and maximum for data distribution. In this case, it is not possible to use other forms of data transformation. As a result of the transformation, the normalized values do not have a minimum and a fixed maximum. Moreover, this technique is not influenced by the presence of outliers, or at least not the same as other methods.