A probability distribution for the outcomes of an experiment. A
probability distribution specifies how likely it is that an experiment
will have any given outcome. For example, a probability distribution
could be used to predict the probability that a token in a document will
have a given type. Formally, a probability distribution can be defined
as a function mapping from samples to nonnegative real numbers, such that
the sum of every number in the function's range is 1.0.
ProbDist
s are often used to model the probability
distribution of the experiment used to generate a frequency
distribution.
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__init__(self)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature |
source code
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float
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prob(self,
sample)
Returns:
the probability for a given sample. |
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float
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logprob(self,
sample)
Returns:
the natural logarithm of the probability for a given sample. |
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any
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max(self)
Returns:
the sample with the greatest probability. |
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list
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Inherited from object :
__delattr__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__repr__ ,
__setattr__ ,
__str__
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