3 ms·

I stand corrected! What are your go-tos?

• rachofsunshine 1y ago
  Not the person you're replying to, but there are tons of models that aren't neural networks. Triplebyte used to use random forests [1] to make a decision to pass or fail a candidate given a set of interview scores. There are a bunch of others, though, like naive Bayes [2] or k-nearest-neighbors [3]. These approaches tend to need a lot less of a training set and a lot less compute than neural networks, at the cost of being substantially less complex in their reasoning (but you don't always need complexity). [1] https://en.wikipedia.org/wiki/Random_forest https://en.wikipedia.org/wiki/Random_forest [2] https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Training https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Trainin... [3] https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm