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Gradient boosted classification and regression trees in python

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wgurecky/pCRTree

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This package implements gradient boosted classification and regression trees. In addition to piecewise constant base learners, piecewise linear regression trees are also implemented.

Gradient boosting is a supervised learning technique applicable to nonlinear regression and classification problems.

pCRTree is split into two subpackages:

  • dtree: Classification and regression trees.
  • boosting: Gradient boosting methods.

Examples

Supports N-Dimensional regression and classification.

Regression

Gradient boosted piecewise linear regression trees:

Example in example/boost_lin_tree_1d.py

Gradient boosted traditional regressing trees:

Quantile regression:

Classification

Example in example/classify_dblgauss.py

Install

Depends:

  • numpy
  • scipy
  • numba

Optional:

  • matplotlib
  • pytest (for testing)
  • sklearn (for example and test benchmarks)

For developers:

$python3 setup.py develop --user

Users:

$python3 setup.py install --user

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Gradient boosted classification and regression trees in python

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