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Commit 618e56f1 authored by Theophile GENTILHOMME's avatar Theophile GENTILHOMME
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Add an example of conf interval in the guide

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2 merge requests!54Refactors the score loading and scripts functionality,!51Confidence intervals
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......@@ -226,8 +226,19 @@ and confidence
value :math:`\alpha` is used as :py:func:`bob.measure.utils.confidence_for_indicator_variable`.
It is based on the cumulative probabilities of the binomial distribution. This
method is quite conservative, meaning that the true coverage rate of a 95%
Clopper–Pearson interval may be well above 95%.
Clopper–Pearson interval may be well above 95%.
For example, we want to evaluate the reliability of a system to
identify registered persons. Let's say that among 10,000 accepted
transactions, 9856 are true matches. The 95% confidence interval for true match
rate is then:
.. doctest:: python
>>> bob.measure.utils.confidence_for_indicator_variable(9856, 10000)
(0.98306835053282549, 0.98784270928084694)
meaning there is a 95% probability that the true match rate is inside :math:`[0.983,
0.988]`.
Plotting
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