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
This project helps data scientists and machine learning engineers understand the inner workings of Gradient Boosting Decision Trees (GBDT) for regression, binary classification, and multi-classification tasks. It takes raw data and outputs a detailed, visualized explanation of how the GBDT algorithm processes the data and makes predictions, allowing for a deeper comprehension of its mechanics.
737 stars. No commits in the last 6 months.
Use this if you are learning about machine learning algorithms and want a clear, step-by-step visual and textual breakdown of how GBDT performs regression or classification.
Not ideal if you are looking for a high-performance, production-ready GBDT implementation, or a tool for automated model training and deployment without needing to delve into the algorithm's specifics.
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737
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196
Language
Python
License
Apache-2.0
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Last pushed
Jun 15, 2019
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