prune: Prune k-gram objects

In sbo: Text Prediction via Stupid Back-Off N-Gram Models

Description

Prune M-gram frequency tables or Stupid Back-Off prediction tables for an M-gram model to a smaller order N.

Usage

prune(object, N, ...)

## S3 method for class 'sbo_kgram_freqs'
prune(object, N, ...)

## S3 method for class 'sbo_predtable'
prune(object, N, ...)

Arguments

object	A kgram_freqs or a sbo_predtable class object.
N	a length one positive integer. N-gram order of the new object.
...	further arguments passed to or from other methods.

Details

This generic function provides a helper to prune M-gram frequency tables or M-gram models, represented by sbo_kgram_freqs and sbo_predtable objects respectively, to objects of a smaller N-gram order, N < M. For k-gram frequency objects, frequency tables for k > N are simply dropped. For sbo_predtable's, the predictions coming from the nested N-gram model are instead retained. In both cases, all other other attributes besides k-gram order (such as the corpus preprocessing function, or the lambda penalty in Stupid Back-Off training) are left unchanged.

Value

an object of the same class of the input object.

Author(s)

Valerio Gherardi

Examples

# Drop k-gram frequencies for k > 2 
freqs <- twitter_freqs
summary(freqs)
freqs <- prune(freqs, N = 2)
summary(freqs)
# Extract a 2-gram model from a larger 3-gram model 
pt <- twitter_predtable
summary(pt)
pt <- prune(pt, N = 2)
summary(pt)

sbo documentation built on Dec. 6, 2020, 1:06 a.m.