how classification scores are interpreted? I would like to know how to interpret  classification scores (i am not sure about the word score or probability, please correct me). For example, for a binary classification positive values are labeled as 1, and -1 for negative ones. Now, is it fair to say that for a score 10 the instance is more likely to be successfully predicted than a score 5, despite the result that can be wrong.
Thanks.
If the scores have values that are higher than 1, I wouldn't call them probabilities. Probabilities should always be between 0 and 1.
And indeed, the higher the score, the more likely an example is to be positive, this is the most natural interpretation of a score.