> Finally, the raw score is run through a squasher function that outputs a probabilistic risk score between 0 and 1, where 1 is the highest risk of fraud. A raw

> Finally, the raw score is run through a squasher function that outputs a probabilistic risk score between 0 and 1, where 1 is the highest risk of fraud. A raw score of 0 corresponds to a risk score of 0.5. I vote that machine learning practitioners shall henceforth refer to the softmax formula as the "squasher function". It's so much more descriptive, kudos to the French!