Commit 2df2c742 authored by Theophile GENTILHOMME's avatar Theophile GENTILHOMME

Aliasing of farfrr() command to fprfnr()

parent ffb23f85
......@@ -10,6 +10,12 @@ from . import plot
from . import calibration
import numpy
def fprfnr(negatives, positives, threshold):
"""Alias for :py:func:`bob.measure.farfrr`"""
return farfrr(negatives, positives, threshold)
def mse (estimation, target):
"""Mean square error between a set of outputs and target values
......
......@@ -34,8 +34,8 @@ methods.
Overview
--------
A classifier is subject to two types of errors, either the real access/signal
is rejected (false negative) or an impostor attack/a false access is accepted
A classifier is subject to two types of errors, either the event one wishes to detect
is rejected (false negative) or an the noise or background one wishes to discard is accepted
(false positive). A possible way to measure the detection performance is to
use the Half Total Error Rate (HTER), which combines the False Negative Rate
(FNR) and the False Positive Rate (FPR) and is defined in the following
......@@ -130,7 +130,7 @@ We do provide a method to calculate the FPR and FNR in a single shot:
.. doctest::
>>> FPR, FNR = bob.measure.farfrr(negatives, positives, T)
>>> FPR, FNR = bob.measure.fprfnr(negatives, positives, T)
The threshold ``T`` is normally calculated by looking at the distribution of
negatives and positives in a development (or validation) set, selecting a
......@@ -171,12 +171,12 @@ calculation of the threshold:
possible threshold is returned. For example, using
:any:`bob.measure.eer_threshold` **will not** give you a threshold where
:math:`FPR == FNR`. Hence, you cannot report :math:`FPR` or :math:`FNR`
instead of :math:`EER`; you should report :math:`(FPR+FNR)/2` instead. This
instead of :math:`EER`; you should report :math:`(FPR+FNR)/2`. This
is also true for :any:`bob.measure.far_threshold` and
:any:`bob.measure.frr_threshold`. The threshold returned by those functions
does not guarantee that using that threshold you will get the requested
:math:`FPR` or :math:`FNR` value. Instead, you should recalculate using
:any:`bob.measure.farfrr`.
:any:`bob.measure.fprfnr`.
.. note::
Many functions in ``bob.measure`` have an ``is_sorted`` parameter, which defaults to ``False``, throughout.
......
......@@ -24,6 +24,7 @@ Single point measurements
.. autosummary::
bob.measure.eer
bob.measure.fprfnr
bob.measure.farfrr
bob.measure.f_score
bob.measure.precision_recall
......
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