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gcForestCS

Description: A python 2.7 implementation of gcForestCS proposed in [1]. A demo implementation of gcForest library as well as some demo client scripts to demostrate how to use the code. The implementation is flexible enough for modifying the model or fit your own datasets.

References:
[1] M. Pang, K. M. Ting, P. Zhao, and Z.-H. Zhou. Improving deep forest by confidence screening. In: Proceedings of the 18th IEEE International Conference on Data Mining (ICDM'18), Singapore, 2018.

ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact .

Requirement: This package is developed with Python 2.7, please make sure all the demendencies are installed, which is specified in requirements.txt.

ATTN2: This package is developed by Mr. Ming Pang (pangm@lamda.nju.edu.cn), which is based on the gcForest package ( http://lamda.nju.edu.cn/code_gcForest.ashx). The readme file and demo roughly explains how to use the codes. For any problem concerning the codes, please feel free to contact Mr. Pang.

Download: [code&data] (62.2MB)
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