Package ML :: Package Composite :: Module BayesComposite
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Module BayesComposite

source code

code for dealing with Bayesian composite models

For a model to be useable here, it should support the following API:

  - _ClassifyExample(example)_, returns a classification

Other compatibility notes:

 1) To use _Composite.Grow_ there must be some kind of builder
    functionality which returns a 2-tuple containing (model,percent accuracy).

 2) The models should be pickleable

 3) It would be very happy if the models support the __cmp__ method so that
    membership tests used to make sure models are unique work.



Classes [hide private]
  BayesComposite
a composite model using Bayesian statistics in the Decision Proxy **Notes** - typical usage: 1) grow the composite with AddModel until happy with it 2) call AverageErrors to calculate the average error values 3) call SortModels to put things in order by either error or count 4) call Train to update the Bayesian stats.
Functions [hide private]
 
CompositeToBayesComposite(obj)
converts a Composite to a BayesComposite if _obj_ is already a BayesComposite or if it is not a _Composite.Composite_ , nothing will be done.
source code
 
BayesCompositeToComposite(obj)
converts a BayesComposite to a Composite.Composite...
source code
Function Details [hide private]

BayesCompositeToComposite(obj)

source code 
converts a BayesComposite to a Composite.Composite