I wanted to ask which method for spamming detection would be more suitable for certain scenario, Naïve Bayes or Artificial Neural Networks, but then I've found 4 sites where Bayes classifiers can be on-topic:
- Stats.SE -> 316 questions (1/3 unanswered),
- DataScience.SE -> 17 questions (4 unanswered)
- Math.SE -> 35 questions (half unanswered),
- CS.SE -> 13 questions about bayesian statistics (no specific tag for classifiers),
- CSTheory.SE -> 17 results on Bayes word, no tags for it at all.
But then I've found that Wikipedia page for Naive Bayes classifier says:
In machine learning, naive Bayes classifiers are ...
It doesn't say in statistics as oppose to 'sampling' (as example), where we can read:
In statistics, quality assurance, and survey methodology, sampling is
Machine learning, a branch of artificial intelligence, is about the construction and study of systems that can learn from data.
To make it more tricky, the machine learning is also a subfield of computer science (as per wiki page). But on the other hand I'm not interested discussing math equations which I'm seeing a lot on CS.SE, because I'm looking for more practical oriented answers, not theories. Secondly they've not specific tags for these classifiers. I'm also not studying this topic (on academia level), but I'm doing this as a hobby, or more specifically, investigating practical problem solutions in my app stack.
Based on above logic, does it mean asking AI.SE is the most suitable place to ask practical questions about spamming detection using Bayes classifiers?