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I have questions regarding data cleaning for machine learning.

Let's say my dataset has three columns with different skewness

For example: label column skewness = 1.500, feature column 1 skewness = 0.0200 and feature column 2 skewness = 0.00

So, do I need to use np.log() for every column or only the column that has high skewness?

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  • $\begingroup$ You don’t necessarily have to use the log transformation even once, so it would help if you said why want your features to lack skewness. $\endgroup$
    – Dave
    Jan 9 at 15:47

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