I'm evaluating the performance of a classifier regarding its false negatives. The classifier performed over 9090 samples, from which 9000 were labeled as negative. I randomly chose 800 samples (out of the 9000) and found that 4 were wrong. This means a 0.5% false negative rate. I also know that the precision (in all the 90 samples labeled positive) is 10%. I want to answer questions like:

  • What's the probability that the false negative rate in all the 9000 labeled negative samples is greater than 2%?
  • What's the margin of error for a 95% confidence?
  • $\begingroup$ by "I also know that the false positive rate (in all the 90 samples labeled positive) is 10%", do you mean that your precision is 90%? Because False Positive Rate is defined on total negatives as base and not total positive predictions (90 in your case). $\endgroup$
    – jdsuryap
    Apr 13 at 19:34
  • $\begingroup$ Yes! I edited it. Thanks. $\endgroup$
    – Raphael
    Apr 13 at 19:47
  • $\begingroup$ Thanks for the clarification. Same question about "This means a 0.5% false negative rate" :-) $\endgroup$
    – jdsuryap
    Apr 13 at 19:49

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