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.
This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Prof. Zhi-Hua Zhou (firstname.lastname@example.org).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.
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.
Both the input and output formats are the same as those used by WEKA.
This package was developed by Mr. Ming Li (email@example.com). This ReadMe file roughly explains the codes. For any problem concerning the code, please feel free to contact Mr. Li.Download