`nltk.BigramAssocMeasures`¶

class nltk.BigramAssocMeasures[source]¶

A collection of bigram association measures. Each association measure is provided as a function with three arguments:

bigram_score_fn(n_ii, (n_ix, n_xi), n_xx)

The arguments constitute the marginals of a contingency table, counting the occurrences of particular events in a corpus. The letter i in the suffix refers to the appearance of the word in question, while x indicates the appearance of any word. Thus, for example:

n_ii counts (w1, w2), i.e. the bigram being scored n_ix counts (w1, ) n_xi counts (, w2) n_xx counts (*, *), i.e. any bigram

This may be shown with respect to a contingency table:

        w1    ~w1
     ------ ------
 w2 | n_ii | n_oi | = n_xi
     ------ ------
~w2 | n_io | n_oo |
     ------ ------
     = n_ix        TOTAL = n_xx

Methods¶

`chi_sq`(n_ii, n_ix_xi_tuple, n_xx)	Scores bigrams using chi-square, i.e.
`dice`(n_ii, n_ix_xi_tuple, n_xx)	Scores bigrams using Dice’s coefficient.
`fisher`(*marginals)	Scores bigrams using Fisher’s Exact Test (Pedersen 1996).
`jaccard`(*marginals)	Scores ngrams using the Jaccard index.
`likelihood_ratio`(*marginals)	Scores ngrams using likelihood ratios as in Manning and Schutze 5.3.4.
`mi_like`(marginals, *kwargs)	Scores ngrams using a variant of mutual information.
`phi_sq`(*marginals)	Scores bigrams using phi-square, the square of the Pearson correlation coefficient.
`pmi`(*marginals)	Scores ngrams by pointwise mutual information, as in Manning and Schutze 5.4.
`poisson_stirling`(*marginals)	Scores ngrams using the Poisson-Stirling measure.
`raw_freq`(*marginals)	Scores ngrams by their frequency
`student_t`(*marginals)	Scores ngrams using Student’s t test with independence hypothesis for unigrams, as in Manning and Schutze 5.3.1.