Freemanzxp/GBDT_Simple_Tutorial
python实现GBDT的回归、二分类以及多分类,将算法流程详情进行展示解读并可视化,庖丁解牛地理解GBDT。Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help readers better understand Gradient Boosting Decision Trees
737 stars. No commits in the last 6 months.
Stars
737
Forks
196
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 15, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Freemanzxp/GBDT_Simple_Tutorial"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python,...
catboost/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for...
stanfordmlgroup/ngboost
Natural Gradient Boosting for Probabilistic Prediction
fabsig/GPBoost
Tree-Boosting, Gaussian Processes, and Mixed-Effects Models
lightgbm-org/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework...