Deep-Forest and gcForest
Deep-Forest is a modernized, actively maintained reimplementation of the original gcForest algorithm, making it the successor framework for practical deep forest applications while gcForest remains the reference implementation of the foundational paper.
About Deep-Forest
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.
About gcForest
kingfengji/gcForest
This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'
This project offers a machine learning method called gcForest, which can be used to classify data. You input a dataset, and it produces predictions or classifications for that data. This is for machine learning practitioners and researchers who need a robust alternative to traditional deep neural networks for classification tasks.
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