- Pure Python custom binary decision tree implementation (notebook) in an OOP manner.
- Example use on AIMA's restaurant dataset.
- Requires Numpy library.
- Creates optimal decision tree structure for a given depth and training dataset.
- Uses entropy minimization to define tree structure.
- Contains rudimentary visualization methods.
-
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Custom binary decision tree implementation in Python (notebook). Example use on AIMA's restaurant dataset.
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sijandh35/Another-Decision-Tree-in-Python
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Custom binary decision tree implementation in Python (notebook). Example use on AIMA's restaurant dataset.
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