nltk.lm.Lidstone

class documentation

class Lidstone(LanguageModel): (source)

Known subclasses: nltk.lm.Laplace

Constructor: Lidstone(gamma, *args, **kwargs)

Provides Lidstone-smoothed scores.

In addition to initialization arguments from BaseNgramModel also requires a number by which to increase the counts, gamma.

Method	`__init__`	Creates new LanguageModel.
Method	`unmasked_score`	Add-one smoothing: Lidstone or Laplace.
Instance Variable	`gamma`	Undocumented

Inherited from LanguageModel:

Method	`context_counts`	Helper method for retrieving counts for a given context.
Method	`entropy`	Calculate cross-entropy of model for given evaluation text.
Method	`fit`	Trains the model on a text.
Method	`generate`	Generate words from the model.
Method	`logscore`	Evaluate the log score of this word in this context.
Method	`perplexity`	Calculates the perplexity of the given text.
Method	`score`	Masks out of vocab (OOV) words and computes their model score.
Instance Variable	`counts`	Undocumented
Instance Variable	`order`	Undocumented
Instance Variable	`vocab`	Undocumented

def __init__(self, gamma, *args, **kwargs): (source) ¶

overrides nltk.lm.api.LanguageModel.__init__

overridden in nltk.lm.Laplace

Creates new LanguageModel.

of creating a new one when training. :type vocabulary: nltk.lm.Vocabulary or None :param counter: If provided, use this object to count ngrams. :type vocabulary: nltk.lm.NgramCounter or None :param ngrams_fn: If given, defines how sentences in training text are turned to ngram

sequences.

Parameters
gamma	Undocumented
*args	Undocumented
ngrams_fn:function or None	Undocumented
pad_fn:function or None	If given, defines how senteces in training text are padded.
vocabulary	If provided, this vocabulary will be used instead
**kwargs	Undocumented

def unmasked_score(self, word, context=None): (source) ¶

overrides nltk.lm.api.LanguageModel.unmasked_score

Add-one smoothing: Lidstone or Laplace.

To see what kind, look at gamma attribute on the class.

gamma = (source) ¶

Undocumented