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COREG

Description: COREG is a co-training style semi-supervised regression algorithm, which employs two kNN regressors using different distance metrics to select the most confidently labeled unlabeled examples for each other.

Reference: Z.-H. Zhou and M. Li. Semi-supervised regression with co-training style algorithms. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(11): 1479-1493.

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 whole WEKA environment (ver 3.4) 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.

Requirement2: To directly use this package, the JAMA package must also be available, unless you can develop the corresponding codes for matrix manipulation at your own risk.

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). This ReadMe file roughly explains the codes. For any problem concerning the code, please feel free to contact Mr. Li.

Download: code (13.5KB)
  Name Size
- COREG.rar 13.61 KB

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