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while reading this post, I came across this claim:

"In practice, however, it’s better to model Σ ( X ) as log Σ ( X ) , as it is more numerically stable to take exponent compared to computing log."

but there is no explanation of why is this true. can enyone explain this?

Moran Reznik
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    It is usually said that log is more stable not exponent: It is about how errors grows, see https://cs.stackexchange.com/questions/91538/why-is-adding-log-probabilities-considered-numerically-stable https://stats.stackexchange.com/questions/174481/why-to-optimize-max-log-probability-instead-of-probability – msuzen Oct 10 '21 at 06:39

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