Question

I want to detect some sort of sentiment orientation for text article. This problem seems related to classification problem, but instead of detecting probabilities of each class (negative, positive, neutral), I want to know some overall score rating, like 0.76 and then classify my article into category that covers the predefined ranges. (e.g. [0.75…1) is positive).

What ml algorithms are suitable for such problem?

Answer 1

As far as I see it, you can do it with one of these two approaches:

1. Use a classifcation algorithm, for binary classifier it gives you
   (p,1-p) – where p is the “chance” the binary classifier is giving it to be “true”.
2. Use linear regression (or other numerical ML algorithm), and give
   the score it returns you. You will label “pos” as 1 and “neg” as 0 when training your algorithm.

Personally, I’d go for the first approach with SVM, since I know it handles large feature space well – and it is likely to be the case in text problems.