nltk.probability.DictionaryProbDist

class documentation

class DictionaryProbDist(ProbDistI): (source)

Constructor: DictionaryProbDist(prob_dict, log, normalize)

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A probability distribution whose probabilities are directly specified by a given dictionary. The given dictionary maps samples to probabilities.

Method __init__ Construct a new probability distribution from the given dictionary, which maps values to probabilities (or to log probabilities, if log is true). If normalize is true, then the probability values are scaled by a constant factor such that they sum to 1.
Method __repr__ Undocumented
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.
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.
Instance Variable _log Undocumented
Instance Variable _max Undocumented
Instance Variable _prob_dict Undocumented

Inherited from ProbDistI:

Method discount Return the ratio by which counts are discounted on average: c*/c
Method generate Return a randomly selected sample from this probability distribution. The probability of returning each sample samp is equal to self.prob(samp).
Constant SUM_TO_ONE True if the probabilities of the samples in this probability distribution will always sum to one.
def __init__(self, prob_dict=None, log=False, normalize=False): (source)
overrides nltk.probability.ProbDistI.__init__

Construct a new probability distribution from the given dictionary, which maps values to probabilities (or to log probabilities, if log is true). If normalize is true, then the probability values are scaled by a constant factor such that they sum to 1.

If called without arguments, the resulting probability distribution assigns zero probability to all values.

def __repr__(self): (source)

Undocumented

def logprob(self, sample): (source)
overrides nltk.probability.ProbDistI.logprob

Return the base 2 logarithm of the probability for a given sample.

Parameters
sample:anyThe sample whose probability should be returned.
Returns
floatUndocumented
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
anyUndocumented
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:anyThe sample whose probability should be returned.
Returns
floatUndocumented
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
listUndocumented
_log = (source)

Undocumented

_max = (source)

Undocumented

_prob_dict = (source)

Undocumented