Explain about the box cox transformation in regression models

Data Science, AI and ML
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Explain about the box cox transformation in regression models.

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The Box-Cox transformation is a generalized “power transformation” that transforms data to make the distribution more normal.

For example, when its lambda parameter is 0, it’s equivalent to the log-transformation.

It’s used to stabilize the variance (eliminate heteroskedasticity) and normalize the distribution.