nltk.probability.CrossValidationProbDist

class documentation

class CrossValidationProbDist(ProbDistI): (source)

Constructor: CrossValidationProbDist(freqdists, bins)

The cross-validation estimate for the probability distribution of the experiment used to generate a set of frequency distribution. The "cross-validation estimate" for the probability of a sample is found by averaging the held-out estimates for the sample in each pair of frequency distributions.

Method	`__init__`	Use the cross-validation estimate to create a probability distribution for the experiment used to generate `freqdists`.
Method	`__repr__`	Return a string representation of this `ProbDist`.
Method	`discount`	Return the ratio by which counts are discounted on average: c*/c
Method	`freqdists`	Return the list of frequency distributions that this `ProbDist` is based on.
Method	`prob`	Return the probability for a given sample. Probabilities are always real numbers in the range [0, 1].
Method	`samples`	Return a list of all samples that have nonzero probabilities. Use `prob` to find the probability of each sample.
Constant	`SUM_TO_ONE`	True if the probabilities of the samples in this probability distribution will always sum to one.
Instance Variable	`_freqdists`	Undocumented
Instance Variable	`_heldout_probdists`	Undocumented

Inherited from ProbDistI:

Method	`generate`	Return a randomly selected sample from this probability distribution. The probability of returning each sample `samp` is equal to `self.prob(samp)`.
Method	`logprob`	Return the base 2 logarithm of the probability for a given sample.
Method	`max`	Return the sample with the greatest probability. If two or more samples have the same probability, return one of them; which sample is returned is undefined.

def __init__(self, freqdists, bins): (source) ¶

overrides nltk.probability.ProbDistI.__init__

Use the cross-validation estimate to create a probability distribution for the experiment used to generate freqdists.

Parameters
freqdists:list(FreqDist)	A list of the frequency distributions generated by the experiment.
bins:int	The number of sample values that can be generated by the experiment that is described by the probability distribution. This value must be correctly set for the probabilities of the sample values to sum to one. If `bins` is not specified, it defaults to `freqdist.B()`.

def __repr__(self): (source) ¶

Return a string representation of this ProbDist.

Returns
str	Undocumented

def discount(self): (source) ¶

overrides nltk.probability.ProbDistI.discount

Return the ratio by which counts are discounted on average: c*/c

Returns
float	Undocumented

def freqdists(self): (source) ¶

Return the list of frequency distributions that this ProbDist is based on.

Returns
list(FreqDist)	Undocumented

def prob(self, sample): (source) ¶

overrides nltk.probability.ProbDistI.prob

Return the probability for a given sample. Probabilities are always real numbers in the range [0, 1].

Parameters
sample:any	The sample whose probability should be returned.
Returns
float	Undocumented

def samples(self): (source) ¶

overrides nltk.probability.ProbDistI.samples

Return a list of all samples that have nonzero probabilities. Use prob to find the probability of each sample.

Returns
list	Undocumented

SUM_TO_ONE: bool = (source) ¶

overrides nltk.probability.ProbDistI.SUM_TO_ONE

True if the probabilities of the samples in this probability distribution will always sum to one.

Value

False

_freqdists = (source) ¶

Undocumented

_heldout_probdists: list = (source) ¶

Undocumented