RSE (Regularized Selective Ensemble) is a selective ensemble learning algorithm for binay classification, which constructs ensemble under the regularization framework. In current version, the graph Laplacian serves as the regularizer, and unlabeled data can also be exploited to improve the performance.

RSE\compute_weight.m
...\demo_rse.m
...\evaluate_rse.m
...\evaluate_rse_ss.m
...\get_error_rate.m
...\Java
...\....\RgStEb
...\....\......\classes
...\....\......\.......\package cache
...\....\......\.......\.............\RgStEb.Base.dep2
...\....\......\.......\RgStEb
...\....\......\.......\......\Base
...\....\......\.......\......\....\BinaryRSE.class
...\....\......\.......\......\....\SemiBinaryRSE.class
...\....\......\src
...\....\......\...\RgStEb
...\....\......\...\......\Base
...\....\......\...\......\....\BinaryRSE.java
...\....\......\...\......\....\SemiBinaryRSE.java
...\LaplacianMatrix.m
RSE
ReadMe.htm

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