LAMDA-NJU/Deep-Forest
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
This tool helps data scientists and machine learning engineers build powerful predictive models using tabular data. You feed it your organized spreadsheet-like data, and it outputs a highly accurate model capable of making predictions or classifications. It's designed for professionals who need effective, scalable, and easy-to-use alternatives to traditional tree-based algorithms.
962 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to build accurate classification or regression models from tabular datasets and want a robust alternative to methods like Random Forest or GBDT, especially for large datasets.
Not ideal if your primary data is structured like images and you intend to use multi-grained scanning for feature extraction.
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962
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167
Language
Python
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Last pushed
Sep 14, 2025
Commits (30d)
0
Dependencies
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