rdkit.ML.DecTree.BuildQuantTree module — The RDKit 2016.09.1 documentation

# rdkit.ML.DecTree.BuildQuantTree module

`rdkit.ML.DecTree.BuildQuantTree.` `BuildQuantTree`(examples, target, attrs, nPossibleVals, nBoundsPerVar, depth=0, maxDepth=-1, exIndices=None, **kwargs)

  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.

`rdkit.ML.DecTree.BuildQuantTree.` `FindBest`(resCodes, examples, nBoundsPerVar, nPossibleRes, nPossibleVals, attrs, exIndices=None, **kwargs)

`rdkit.ML.DecTree.BuildQuantTree.` `QuantTreeBoot`(examples, attrs, nPossibleVals, nBoundsPerVar, initialVar=None, maxDepth=-1, **kwargs)

  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.

`rdkit.ML.DecTree.BuildQuantTree.` `TestQuantTree`()

  Testing code for named trees

  The created pkl file is required by the unit test code.

`rdkit.ML.DecTree.BuildQuantTree.` `TestQuantTree2`()

  testing code for named trees

  The created pkl file is required by the unit test code.

`rdkit.ML.DecTree.BuildQuantTree.` `TestTree`()

  testing code for named trees