Python Machine Learning By Example - Second Edition

Power transform

Power transforms are functions that we can use to transform numerical features into a more convenient form to conform better to a normal distribution. A very common transform for value, which vary by orders of magnitude, is to take the logarithm. Taking the logarithm of a zero and negative values isn't defined, so we may need to add a constant to all of the values of the related feature before taking the logarithm. We can also take the square root for positive values, square the values, or compute any other power we like.

Another useful transform is the Box-Cox transformation, named after its creators. The Box-Cox transformation attempts to find the best power needed to transform the original data into data that's closer to ...