Author:
Peng Hao,Zhou Jian,Liu Shenglan
Publisher
Springer Nature Singapore
Reference11 articles.
1. Chen, X.J., et al.: Local adaptive projection framework for feature selection of labeled and unlabeled data. IEEE Trans. Neural Netw. Learn. Syst. 29(12), 6362–6373 (2018)
2. Krishnapuram, B., Harternink, A.J., Carin, L., Figueiredo, M.A.T.: A Bayesian approach to joint feature selection and classifier design. IEEE Trans. Pattern Anal. Mach. Intell. 26(9), 1105–1111 (2004)
3. Liu, H., Yu, L.: Toward integrating feature selection algorithms for classification and clustering. IEEE Trans. Knowl. Data Eng. 17(4), 491–502 (2005)
4. Wolf, L., Shashua, A.: Feature selection for unsupervised and supervised inference: the emergence of sparsity in a weight based approach. J. Mach. Learn. Res. 6, 1855–1887 (2005)
5. Liu, S.L., Feng, L., Qiao, H.: Scatter balance: An angle-based supervised dimensionality reduction. IEEE Trans. Neural Netw. Learn. Syst. 26(2), 277–289 (2015)