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Comment by pwf | Hacker News Reader

Is there a bug in the train function? Using 'lambda: 1' for the default dict along with '+=' means that the first time a feature is encountered, the value is set to 2.

  In [1]: from collections import defaultdict

  In [2]: d = defaultdict(lambda: 1)

  In [3]: d['foo'] += 1

  In [4]: d['foo']
  Out[4]: 2

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I think the code is correct. To implement smoothing, you want to add 1 to the count of every word, regardless of whether it appears in the training data or not.

That is to say, a word that appears once should get a count of 2, and word that doesn't appear at all should get a count of 1.

That makes sense, thanks!

I should learn to read...

This is a perfect example of where a (short) code comment would be helpful. The "lambda: 1" a notable piece of code, but it's hard to tell that at a glance.

no it's not, it's perfectly clearly documented in code. The smoothing is common practice in this area of software engineering.

And yet this is written for people who aren't familiar with this area of software engineering. It's stated so right at the top of the article.

nonsense, any software dev that can't follow a lambda that adds 1 should be taken outside and shot.

When Norvig says talks of regular folks, he means people with 1/10th his IQ, which is still the top 1%. Norvig is so far out there on the IQ scale that I find it funny when some noob says he's found a bug!

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