Package rdkit :: 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
Functions [hide private]
 
CompositeToBayesComposite(obj)
converts a Composite to a BayesComposite
source code
 
BayesCompositeToComposite(obj)
converts a BayesComposite to a Composite.Composite
source code
Variables [hide private]
  __package__ = 'rdkit.ML.Composite'

Imports: numpy, Composite


Function Details [hide private]

CompositeToBayesComposite(obj)

source code 
converts a Composite to a BayesComposite

if _obj_ is already a BayesComposite or if it is not a _Composite.Composite_ ,
 nothing will be done.