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Imports: numpy, random, QuantTree, ID3, entropy, Quantize, range
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**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. |
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. |
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