Package rdkit :: Package ML :: Package Composite :: Module BayesComposite :: Class BayesComposite

[hide private]
[frames] | no frames]

# Class BayesComposite

source code

             object --+
                      |
    Composite.Composite --+
                          |
                         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.

Instance Methods | [hide private]

Train(self, data, verbose=0) | source code

ClassifyExample(self, example, threshold=0, verbose=0, appendExample=0) classifies the given example using the entire composite | source code

__init__(self) x.__init__(...) initializes x; see help(type(x)) for signature | source code

Inherited from `Composite.Composite`: `AddModel`, `AverageErrors`, `ClearModelExamples`, `CollectVotes`, `GetActivityQuantBounds`, `GetAllData`, `GetCount`, `GetDataTuple`, `GetDescriptorNames`, `GetError`, `GetInputOrder`, `GetModel`, `GetQuantBounds`, `GetVoteDetails`, `Grow`, `MakeHistogram`, `Pickle`, `QuantizeActivity`, `QuantizeExample`, `SetActivityQuantBounds`, `SetCount`, `SetDataTuple`, `SetDescriptorNames`, `SetError`, `SetInputOrder`, `SetModel`, `SetModelFilterData`, `SetQuantBounds`, `SortModels`, `__getitem__`, `__len__`, `__str__`

Inherited from `Composite.Composite` (private): `_RemapInput`

Inherited from `object`: `__delattr__`, `__format__`, `__getattribute__`, `__hash__`, `__new__`, `__reduce__`, `__reduce_ex__`, `__repr__`, `__setattr__`, `__sizeof__`, `__subclasshook__`

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### ClassifyExample(self, example, threshold=0, verbose=0, appendExample=0)

source code

    classifies the given example using the entire composite

    **Arguments**

     - example: the data to be classified

     - threshold:  if this is a number greater than zero, then a
        classification will only be returned if the confidence is
        above _threshold_.  Anything lower is returned as -1.

    **Returns**

      a (result,confidence) tuple

Overrides: Composite.Composite.ClassifyExample

### __init__(self)
(Constructor)

source code

    x.__init__(...) initializes x; see help(type(x)) for signature

Overrides: object.__init__
  (inherited documentation)