nltk.probability.LidstoneProbDist

class documentation

class LidstoneProbDist(ProbDistI): (source)

Known subclasses: nltk.probability.ELEProbDist, nltk.probability.LaplaceProbDist

Constructor: LidstoneProbDist(freqdist, gamma, bins)

The Lidstone estimate for the probability distribution of the experiment used to generate a frequency distribution. The "Lidstone estimate" is parameterized by a real number gamma, which typically ranges from 0 to 1. The Lidstone estimate approximates the probability of a sample with count c from an experiment with N outcomes and B bins as c+gamma)/(N+B*gamma). This is equivalent to adding gamma to the count for each bin, and taking the maximum likelihood estimate of the resulting frequency distribution.

Method	`__init__`	Use the Lidstone estimate to create a probability distribution for the experiment used to generate `freqdist`.
Method	`__repr__`	Return a string representation of this `ProbDist`.
Method	`discount`	Return the ratio by which counts are discounted on average: c*/c
Method	`freqdist`	Return the frequency distribution that this probability distribution is based on.
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.
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	`_bins`	Undocumented
Instance Variable	`_divisor`	Undocumented
Instance Variable	`_freqdist`	Undocumented
Instance Variable	`_gamma`	Undocumented
Instance Variable	`_N`	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.

def __init__(self, freqdist, gamma, bins=None): (source) ¶

overrides nltk.probability.ProbDistI.__init__

overridden in nltk.probability.ELEProbDist, nltk.probability.LaplaceProbDist

Use the Lidstone estimate to create a probability distribution for the experiment used to generate freqdist.

Parameters
freqdist:FreqDist	The frequency distribution that the probability estimates should be based on.
gamma:float	A real number used to parameterize the estimate. The Lidstone estimate is equivalent to adding gamma to the count for each bin, and taking the maximum likelihood estimate of the resulting frequency distribution.
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) ¶

overridden in nltk.probability.ELEProbDist, nltk.probability.LaplaceProbDist

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 freqdist(self): (source) ¶

Return the frequency distribution that this probability distribution is based on.

Returns
FreqDist	Undocumented

def max(self): (source) ¶

overrides nltk.probability.ProbDistI.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.

Returns
any	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

_bins = (source) ¶

Undocumented

_divisor: int = (source) ¶

Undocumented

_freqdist = (source) ¶

Undocumented

_gamma: int = (source) ¶

Undocumented

_N = (source) ¶

Undocumented