woods 0.1.0

Decision Trees Ensembles

Woods: Decision Tree Ensembles

Currently implemented algorithms:

1. Partially randomized decision tree (variance minimization).
2. Gradient Boosting of decision trees (MSE minimization).
3. Average ensemble of GBM.
4. Deep Gradient Boosting (of Average ensembles of GBM).

TODO

• Implement median-split, best-split decision tree;
• Provide optional min&max search based on pre-sorting (find min&max of array[indices]);
• Add different loss-functions, ranking support.

Installation

Build environment

1. Install rustup.
2. Set up nightly toolchain:

rustup toolchain install nightly
rustup default nightly

Install Python extension

Run setup.py:

python setup.py install --user

Note that --user option is used to install package locally.

Build documentation

Go to rust dir and run:

cargo doc --lib

Docs will be placed in target/doc/woods/index.html.