https://github.com/shigekikarita/d-tree
Decision tree library for D
https://github.com/shigekikarita/d-tree
decision-tree gradient-boosting mir numir
Last synced: 4 months ago
JSON representation
Decision tree library for D
- Host: GitHub
- URL: https://github.com/shigekikarita/d-tree
- Owner: ShigekiKarita
- License: bsl-1.0
- Created: 2018-02-06T14:39:13.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-02-17T04:19:01.000Z (over 8 years ago)
- Last Synced: 2025-08-04T04:00:05.328Z (11 months ago)
- Topics: decision-tree, gradient-boosting, mir, numir
- Language: D
- Size: 2.1 MB
- Stars: 4
- Watchers: 3
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.org
- License: LICENSE
Awesome Lists containing this project
README
* Decision tree library for D
[[https://travis-ci.org/ShigekiKarita/d-tree][file:https://travis-ci.org/ShigekiKarita/d-tree.svg?branch=master]]
[[https://codecov.io/gh/ShigekiKarita/d-tree][file:https://codecov.io/gh/ShigekiKarita/d-tree/branch/master/graph/badge.svg]]
[[https://code.dlang.org/packages/d-graphviz][file:https://img.shields.io/dub/v/d-graphviz.svg]]
getting started
#+begin_src
$ curl https://dlang.org/install.sh | bash -s # install dlang compiler
$ source ~/dlang//activate
$ cd example/plot_dtree_boundary
$ dub run
$ xdg-open *.png
#+end_src
- single decision tree classification result
[[./example/plot_boundary/plot_dtree_gini.png]]
- random forest classification result
[[./example/plot_boundary/plot_forest_gini.png]]
- single decision tree regression result in `example/sin_regression`
[[./example/sin_regression/plot_tree.png]]
- random forest regression result in `example/sin_regression`
[[./example/sin_regression/plot_forest.png]]
** Roadmap
- DONE Classification tree (2/6)
- DONE Random forest (2/7)
- DONE Regression tree (2/9)
- DONE Gradient boosting (2/14)
- TODO bootstrap sampling in RF
- TODO Parallel processing
- TODO Serialization
- TODO Support libsvm format
** Reference
- [[https://web.stanford.edu/~hastie/Papers/ESLII.pdf][The Elements of Statistical Learning 2nd Edition]]
- [[https://arxiv.org/pdf/1603.02754.pdf][XGBoost: A Scalable Tree Boosting System]]