Natural Language Processing with Python by Steven Bird Ewan Klein and Edward Loper

Author:Steven Bird, Ewan Klein, and Edward Loper
Language: eng
Format: mobi
Tags: COMPUTERS / Programming Languages / Python
Publisher: O’Reilly Media
Published: 2009-06-12T04:00:00+00:00

Individual features make their contribution to the overall decision by “voting against” labels that don’t occur with that feature very often. In particular, the likelihood score for each label is reduced by multiplying it by the probability that an input value with that label would have the feature. For example, if the word run occurs in 12% of the sports documents, 10% of the murder mystery documents, and 2% of the automotive documents, then the likelihood score for the sports label will be multiplied by 0.12, the likelihood score for the murder mystery label will be multiplied by 0.1, and the likelihood score for the automotive label will be multiplied by 0.02. The overall effect will be to reduce the score of the murder mystery label slightly more than the score of the sports label, and to significantly reduce the automotive label with respect to the other two labels. This process is illustrated in Figures 6-7 and 6-8.

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