Metadata-Version: 2.1
Name: woods
Version: 0.1.0
Summary: Decision Trees Ensembles
Home-page: https://github.com/andruekonst/Woods
Author: Andrei V. Konstantinov
Author-email: andrue.konst@gmail.com
License: UNKNOWN
Description: # 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`.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
