Package nltk :: Package metrics :: Module scores

Module scores

Functions

accuracy(reference, test)
Given a list of reference values and a corresponding list of test values, return the fraction of corresponding values that are equal.

source code

float or None

precision(reference, test)
Given a set of reference values and a set of test values, return the fraction of test values that appear in the reference set.

source code

float or None

recall(reference, test)
Given a set of reference values and a set of test values, return the fraction of reference values that appear in the test set.

source code

float or None

f_measure(reference, test, alpha=0.5)
Given a set of reference values and a set of test values, return the f-measure of the test values, when compared against the reference values.

source code

log_likelihood(reference, test)
Given a list of reference values and a corresponding list of test probability distributions, return the average log likelihood of the reference values, given the probability distributions.

source code

tuple

approxrand(a, b, **kwargs)
Returns an approximate significance level between two lists of independently generated test values.

source code

demo()

source code

Variables

[hide private]

betai = None

Function Details

[hide private]

accuracy(reference, test)

source code

Given a list of reference values and a corresponding list of test values, return the fraction of corresponding values that are equal. In particular, return the fraction of indices 0<i<=len(test) such that test[i] == reference[i].

Parameters:

reference (list) - An ordered list of reference values.
test (list) - A list of values to compare against the corresponding reference values.

Raises:

ValueError - If reference and length do not have the same length.

precision(reference, test)

source code

Given a set of reference values and a set of test values, return the fraction of test values that appear in the reference set. In particular, return |reference∩test|/|test|. If test is empty, then return None.

Parameters:

reference (Set) - A set of reference values.
test (Set) - A set of values to compare against the reference set.

Returns: float or None

recall(reference, test)

source code

Given a set of reference values and a set of test values, return the fraction of reference values that appear in the test set. In particular, return |reference∩test|/|reference|. If reference is empty, then return None.

Parameters:

reference (Set) - A set of reference values.
test (Set) - A set of values to compare against the reference set.

Returns: float or None

f_measure(reference, test, alpha=0.5)

source code

Given a set of reference values and a set of test values, return the f-measure of the test values, when compared against the reference values. The f-measure is the harmonic mean of the precision and recall, weighted by alpha. In particular, given the precision p and recall r defined by:

p = |reference∩test|/|test|
r = |reference∩test|/|reference|

The f-measure is:

1/(alpha/p + (1-alpha)/r)

If either reference or test is empty, then f_measure returns None.

Parameters:

reference (Set) - A set of reference values.
test (Set) - A set of values to compare against the reference set.

Returns: float or None

log_likelihood(reference, test)

source code

Given a list of reference values and a corresponding list of test probability distributions, return the average log likelihood of the reference values, given the probability distributions.

Parameters:

reference (list) - A list of reference values
test (list of ProbDistI) - A list of probability distributions over values to compare against the corresponding reference values.

approxrand(a, b, **kwargs)

source code

Returns an approximate significance level between two lists of independently generated test values.

Approximate randomization calculates significance by randomly drawing from a sample of the possible permutations. At the limit of the number of possible permutations, the significance level is exact. The approximate significance level is the sample mean number of times the statistic of the permutated lists varies from the actual statistic of the unpermuted argument lists.

Parameters:

a (list) - a list of test values
b (list) - another list of independently generated test values

Returns: tuple

a tuple containing an approximate significance level, the count of the number of times the pseudo-statistic varied from the actual statistic, and the number of shuffles