What is power transformation in machine learning?

Date:2023-01-07
Power transformation is a data pre-processing technique used to help stabilize variance and make data more normal distribution-like. It is used to reduce the effect of outliers, improve the symmetry of distributions and make the data more amenable to modeling. It involves applying a power or exponent to each value in the data so that the transformed values follow a more normal distribution. Power transformation can be used to better fit the data to a machine learning algorithm, improve its accuracy and performance or modify the interpretation of model results.
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