January 2020
Beginner to intermediate
372 pages
10h
English
Content preview from Python Feature Engineering Cookbook
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Implementing maximum absolute scaling
Maximum absolute scaling scales the data to its maximum value; that is, it divides every observation by the maximum value of the variable:
The result of the preceding transformation is a distribution in which the values vary approximately within the range of -1 to 1. In this recipe, we will implement maximum absolute scaling with scikit-learn.
Scikit-learn recommends using this transformer on data that is centered at zero or on sparse data.
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