In Mathematics for Machine Learning (page 336), the authors state that centering the data (subtracting from the data its the empirical mean) reduces the risk of numerical problems.

Which numerical problems are likely to arise if the data is not centered? How does centering mitigate the numerical problems that would otherwise aris?



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