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Way to evaluate a "score" for models

Open Sentdex opened this issue 6 years ago • 1 comments

A model's overall success is determined not just by average accuracy, because some wrong classifications are worse than others.

Example: Target: Right Predicted: Left

is worse than: Target: Right Predicted: None

Sentdex avatar Nov 11 '19 02:11 Sentdex

@Sentdex we might be able to get away with a Dense(1, activation='tanh') output and multiply this, with some speed/acceleration scalars, directly to the x-position of your object on screen.

-1 would be "go left more", +1 would be "go right more", and outputs closer to 0 would do nothing or return to center. This way, Left <-> Right misses would be more distant than Right<->None or Left<->None misses.

You could expand on this to do xy translations with a Dense(2, activation='tanh'), xyz's with a Dense(3, activation='tanh'), etc.

What do you think?

moznpan avatar Nov 17 '19 22:11 moznpan