The tool kit contains GSGBN's software for ICDM14 paper *"Learning Sparse Gaussian Bayesian Networks by Variable Grouping"*.
#INSTALL
Exract the package, then use make to compile the source code.
- $ git clone https://github.com/ch11y/GSGBN/
- $ cd GSGBN
- $ make
Find the excutive file in ./bin/.
#RUN
##Usage:
GSGBN -i input.txt -l1 1.0 -l2 0.1 -num 10 -thr 0.1
##Options:
-i, an m * n matrix with m samples and n variables;
-l1, the regularization parameter lambda1 for sparsity;
-l2, the regularization parameter lambda2*n is used for grouping;
-num, number of rounds for enumerating DAGs;
-thr, threshold for filtering
##*Notes*
***The package does not contain the process of cross validation.***
##Contact:
Jie Yang (Email: jyang2@cs.hku.hk), Department of Computer Science, The University of Hong Kong.
#Reference
Jie Yang, Henry C.M. Leung, S.M. Yiu, Yunpeng Cai, Francis Y.L. Chin, *Learning Sparse Gaussian Bayesian Networks by Variable Grouping*, The IEEE International Conference on Data Mining (ICDM 2014).
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