sklearn-oblique-tree
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AndriyMulyar
a python interface to OC1 and other oblique decision tree implementations
Thank you for providing this useful package of the oblique trees. It's really useful to some academic users like me who currently try to develop a new multivariate tree model....
Windows10, 64bit, Python2.7 (anaconda) pip install git+https://github.com/AndriyMulyar/sklearn-oblique-tree --no-deps C:\Users\bscully1\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\amd64\cl.exe /c /nologo /Ox /MD /W3 /GS- /DNDEBUG -IC:\ProgramData\Anaconda2\lib\site-packages\numpy\core\include -I. -IC:\ProgramData\Anaconda2\include -IC:\ProgramData\Anaconda2\PC /Tcsklearn_oblique_tree/oblique/_oblique.c /Fobuild\temp.win-amd64-2.7\Release\sklearn_oblique_tree/oblique/_oblique.obj -w cl : Command line...
The original implementation contains an excellent visualization tool. Extend it into the python interface.
The ability to switch between impurity metrics is implemented in the underlying implementation. Interface it with python.
Implement predict_prob with something like laplace smoothing. This is trivial but will support the use of the classifier directly in scikit-learns random forest which averages class predictions over-top of class...
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a python interface to OC1 and other oblique decision tree implementations