#
*Why
is it better to compute likelihood and probability values in log space?*

###
__Question:__

### Why is it better to computer likelihood and probability values in log space?

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__Answer:__

Computing
likelihood and probability values in log space solves the underflow problem (

*refer below*). Moreover, when computing in log space, we can replace the multiplication operations by addition operations, which are usually faster than multiplication operations on a modern computer.###
**What is Underflow?**

**What is Underflow?**

Joint probability distribution often involves multiplying small individual probabilities.
Many probabilistic algorithms involve multiplying probabilities of
individual data points that takes the result very close to zero. This is
called as underflow.

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__Related questions:__

__Related questions:__

**Why is it better to compute likelihood and probability values in log space?**

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