nltk.probability.MLEProbDist¶
- class nltk.probability.MLEProbDist[source]¶
Bases:
ProbDistIThe maximum likelihood estimate for the probability distribution of the experiment used to generate a frequency distribution. The “maximum likelihood estimate” approximates the probability of each sample as the frequency of that sample in the frequency distribution.
- __init__(freqdist, bins=None)[source]¶
Use the maximum likelihood 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.
- freqdist()[source]¶
Return the frequency distribution that this probability distribution is based on.
- Return type
- prob(sample)[source]¶
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.
- Return type
float
- max()[source]¶
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.
- Return type
any
- samples()[source]¶
Return a list of all samples that have nonzero probabilities. Use
probto find the probability of each sample.- Return type
list
- SUM_TO_ONE = True¶
True if the probabilities of the samples in this probability distribution will always sum to one.
- discount()¶
Return the ratio by which counts are discounted on average: c*/c
- Return type
float
- generate()¶
Return a randomly selected sample from this probability distribution. The probability of returning each sample
sampis equal toself.prob(samp).
- logprob(sample)¶
Return the base 2 logarithm of the probability for a given sample.
- Parameters
sample (any) – The sample whose probability should be returned.
- Return type
float