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NeC4.5

Description: NeC4.5 is a variant of C4.5 decision tree, which could generate decision trees more accurate than standard C4.5 decision trees, through regarding a neural network ensemble as a pre-process of C4.5 decision tree.

Reference: Z.-H. Zhou and Y. Jiang. NeC4.5: Neural ensemble based C4.5. IEEE Transactions on Knowledge and Data Engineering, 2004, vol.16, no.6, pp.770-773.

ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Prof. Zhi-Hua Zhou (zhouzh@nju.edu.cn).

Requirement: To use this package, the WEKA environment must be available. Refer: I.H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, San Francisco, CA, 2000.

Data format: Both the input and output formats are the same as those used by WEKA.

ATTN2: This package was developed by Mr. Ming Li (lim@lamda.nju.edu.cn). There is a ReadMe file roughly explaining the codes. But for any problem concerning the code, please feel free to contact Mr. Li. Please note that since the C4.5 routine used by this package is its reimplementation in WEKA, the performance of the package would be slightly different from that reported in the paper.

Download: code (7.8Kb)
  Name Size
- NeC45.zip 7.85 KB

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