Fine-Tuning Classifiers; Poor Performance

API
6

I see.

Personally, if I find myself to decide on the better of 2 - I don’t consider it a binary classification.

For me binary classification is when you put a system in a “black and white” world, show it a thing and all a question : is this black? Y/N.

Here, the “better” must be defined and evaluated before answering “which is better”.

I would approach it in two steps:

  1. Evaluate:
  • define criteria of what is ideal
  • note sample based on criteria (e.g. 0-9)
  1. Compare:
  • sort samples by note
  • find the best

And the above before even going into parameters mess…

But then, I don’t have all the context and reasons to judge.

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