Package rdkit :: Package ML :: Package DecTree :: Module BuildQuantTree
[hide private]
[frames] | no frames]

Module BuildQuantTree

source code



Functions [hide private]
 
FindBest(resCodes, examples, nBoundsPerVar, nPossibleRes, nPossibleVals, attrs, exIndices=None, **kwargs) source code
 
BuildQuantTree(examples, target, attrs, nPossibleVals, nBoundsPerVar, depth=0, maxDepth=-1, exIndices=None, **kwargs)
**Arguments**
source code
 
QuantTreeBoot(examples, attrs, nPossibleVals, nBoundsPerVar, initialVar=None, maxDepth=-1, **kwargs)
Bootstrapping code for the QuantTree
source code
 
TestTree()
testing code for named trees
source code
 
TestQuantTree()
testing code for named trees
source code
 
TestQuantTree2()
testing code for named trees
source code
Variables [hide private]
  __package__ = 'rdkit.ML.DecTree'

Imports: numpy, random, QuantTree, ID3, entropy, Quantize, range


Function Details [hide private]

BuildQuantTree(examples, target, attrs, nPossibleVals, nBoundsPerVar, depth=0, maxDepth=-1, exIndices=None, **kwargs)

source code 

**Arguments**

  - examples: a list of lists (nInstances x nVariables+1) of variable
    values + instance values

  - target: an int

  - attrs: a list of ints indicating which variables can be used in the tree

  - nPossibleVals: a list containing the number of possible values of
               every variable.

  - nBoundsPerVar: the number of bounds to include for each variable

  - depth: (optional) the current depth in the tree

  - maxDepth: (optional) the maximum depth to which the tree
               will be grown
**Returns**

 a QuantTree.QuantTreeNode with the decision tree

**NOTE:** This code cannot bootstrap (start from nothing...)
      use _QuantTreeBoot_ (below) for that.

QuantTreeBoot(examples, attrs, nPossibleVals, nBoundsPerVar, initialVar=None, maxDepth=-1, **kwargs)

source code 
Bootstrapping code for the QuantTree

If _initialVar_ is not set, the algorithm will automatically
 choose the first variable in the tree (the standard greedy
 approach).  Otherwise, _initialVar_ will be used as the first
 split.