When given different images of the same people, the algorithm could determine their identity with 57% accuracy, or 85% percent when given five chances.
Wait a damn moment. How did we get 85% from five consecutive attempts? I assume the algorithm’s top match can either be right or wrong (there is no inbetween). Let final result be the rounded average of the five attempts, the final probability of being right should be 63% not 85%.
The probability of making 3 right guesses and then a wrong guess is P(TTTFF)=.57^3*(1-.57)^2=3.42% Since order doesn’t matter we use nCr to multiply this value by all the different orderings of the letters. (5 C 3)=5!/(3!2!)=10. So the probability of making exactly 3 right attempts is 103.42%=34.2%. Similarly for P(TTTTF)=.57^4*(1-.57)=4.54% and there are obviously 5 ways to do this so the total probability of this is 22.69%. The probability of getting all 5 guesses right is just .57^5=6.02% and there is only one way to do this. Since the rounded average will be true if any of these ways happens we add the probabilities together to get 63%. Where did the 85% number come from?
