References:
√ BEPILD: Zhu, Y., Wang, Z., Zha, H., & Gao, D. (2018). Boundary-Eliminated Pseudoinverse Linear Discriminant for Imbalanced Problems. IEEE Transactions on Neural Networks and Learning Systems, 29(6), 2581-2594.
√ FCIMLM: Zhu, Y., Wang, Z., & Gao, D. (2016). Matrixized Learning Machine with Feature-Clustering Interpolation. Neural Processing Letters, 44(2), 291-306.
√ FLDS1(IFLD): Daqi, G., Jun, D., & Changming, Z. (2014). Integrated Fisher linear discriminants: An empirical study. Pattern Recognition, 47(2), 789-805.
√ GFRNN: Zhu, Y., Wang, Z., & Gao, D. (2015). Gravitational fixed radius nearest neighbor for imbalanced problem. Knowledge-Based Systems, 90, 224-238.
√ GLMatMHKS: Wang, Z., Zhu, Y., Gao, D., & Guo, W. (2014). Globalized and localized matrix-pattern-oriented classification machine. Applied Soft Computing, 25, 379-390.
√ GMFLLM: Zhu, Y., Wang, Z., Li, D., & Gao, D. (2017). GMFLLM: A general manifold framework unifying three classic models for dimensionality reduction. Engineering Applications of Artificial Intelligence, 65, 421-432.
√ MatMHKS: Chen, S., Wang, Z., & Tian, Y. (2007). Matrix-pattern-oriented Ho–Kashyap classifier with regularization learning. Pattern Recognition, 40(5), 1533-1543.
√ MHKS: Łęski, J. (2003). Ho–Kashyap classifier with generalization control. Pattern Recognition Letters, 24(14), 2281-2290.
√ MLMMPC: Zhu, Y., Wang, Z., & Gao, D. (2015). Matrixized learning machine with modified pairwise constraints. Pattern Recognition, 48(11), 3797-3809.
√ RFLDS1/S2: Zhu, Y., Wang, Z., Cao C., & Gao, D. (2018) Regularized fisher linear discriminant through two threshold variation strategies for imbalanced problems. Knowledge-Based Systems, 000, 1-17.
√ SFSS-RF: Under review.
√ UMultiV-MHKS: Wang, Z., Zhu, Y., Liu, W., Chen, Z., & Gao, D. (2014). Multi-view learning with universum. Knowledge-Based Systems, 70, 376-391.