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Underflow Prevention: using logs

  • Multiplying lots of probabilities, which are between 0 and 1 by definition, can result in floating-point underflow.

  • Since log(xy) = log(x) + log(y), it is better to perform all computations by summing logs of probabilities rather than multiplying probabilities.

  • Class with highest final un-normalized log probability score is still the most probable.

  • Note that model is now just max of sum of weights…

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