Accès libre

Statistical method for clustering high-dimensional data based on fuzzy mathematical modeling

   | 11 déc. 2023
À propos de cet article

Citez

Hu, S., Wang, R., & Ye, Y. (2021). Interactive information bottleneck for high-dimensional co-occurrence data clustering. Applied Soft Computing(111-), 111. Search in Google Scholar

Bouveyron, C., Girard, S., & Schmid, C. (2007). High-dimensional data clustering. Computational Statistics & Data Analysis, 52(1), 502-519. Search in Google Scholar

Mardia, K. V., Wiechers, H., Eltzner, B., & Huckemann, S. F. (2022). Principal component analysis and clustering on manifolds. Journal of Multivariate Analysis, 188. Search in Google Scholar

C, M. D. A. B., A, E. F., D, A. L. A., & D, A. R. A. (2021). Automatic topography of high-dimensional data sets by non-parametric density peak clustering - sciencedirect. Information Sciences. Search in Google Scholar

Kim, Y., Telea, A. C., Trager, S. C., & Roerdink, J. B. (2022). Visual cluster separation using high-dimensional sharpened dimensionality reduction:. Information Visualization, 21(3), 197-219. Search in Google Scholar

Zhang, J., Lu, G., Li, J., & Li, C. (2021). An ensemble classification method for high-dimensional data using neighborhood rough set. Complexity(Pt.33), 2021. Search in Google Scholar

Du, H., Ni, Y., & Wang, Z. (2021). An improved algorithm based on fast search and find of density peak clustering for high-dimensional data. Wireless Communications and Mobile Computing. Search in Google Scholar

André L.V. Coelho, & Sandes, N. C. (2021). Data clustering via cooperative games: a novel approach and comparative study. Information Sciences, 545, 791-812. Search in Google Scholar

Zhong, G., & Pun, C. M. (2023). Simultaneous laplacian embedding and subspace clustering for incomplete multi-view data. Knowledge-Based Systems, 262, 110244-. Search in Google Scholar

Wang, X., Guo, D., & Cheng, P. (2021). Support structure representation learning for sequential data clustering. Pattern Recognition(2), 108326. Search in Google Scholar

Huang, D., Wang, C. D., Lai, J. H., & Kwoh, C. K. (2021). Toward multi-diversified ensemble clustering of high-dimensional data: from subspaces to metrics and beyond. IEEE Transactions on Cybernetics. Search in Google Scholar

Zhao, J., He, X., Li, H., & Lu, L. (2021). An adaptive optimization algorithm based on clustering analysis for return multi-flight-phase of vtvl reusable launch vehicle. Acta Astronautica, 183(1). Search in Google Scholar

Gherbaoui, R., Ouali, M., & Nacéra Benamrane. (2021). Generation of gaussian sets for clustering methods assessment. Data & Knowledge Engineering, 131-132(4), 101876. Search in Google Scholar

Barshandeh, S., Dana, R., & Eskandarian, P. (2022). A learning automata-based hybrid mpa and js algorithm for numerical optimization problems and its application on data clustering. Knowledge-based systems(Jan.25), 236. Search in Google Scholar

Teng, YueyangQi, ShouliangHan, FangfangXu, LishengYao, YudongQian, Wei. (2021). Two graph-regularized fuzzy subspace clustering methods. Applied Soft Computing, 100(1). Search in Google Scholar

Wu, Z., Su, C., Yin, M., Ren, Z., & Xie, S. (2021). Subspace clustering via stacked independent subspace analysis networks with sparse prior information. Pattern Recognition Letters(3). Search in Google Scholar

Karimzadeh, A., Sabeti, S., & Shoghli, O. (2021). Optimal clustering of pavement segments using k-prototype algorithm in a high-dimensional mixed feature space. Journal of management in engineering(4), 37. Search in Google Scholar

Zsolt T. Kosztyán a b c, András Telcs a b d, & János Abonyi e. (2021). A multi-block clustering algorithm for high dimensional binarized sparse data. Expert Systems with Applications, 191. Search in Google Scholar

Chen, J., Mao, H., Wang, Z., & Zhang, X. (2021). Low-rank representation with adaptive dictionary learning for subspace clustering. Knowledge-Based Systems, 223(13), 107053. Search in Google Scholar

Yijia, L., Jonathan, N., Anastasiu, D. C., & Arriaga, E. A. (2023). Costal: an accurate and scalable graph-based clustering algorithm for high-dimensional single-cell data analysis. Briefings in Bioinformatics(3), 3. Search in Google Scholar

Tan, D., Peng, X., Wang, Q., Zhong, W., & Mahalec, V. (2021). Automatic determining optimal parameters in multi-kernel collaborative fuzzy clustering based on dimension constraint. Neurocomputing. Search in Google Scholar

Huang, R., Xiao, R., Zhu, W., Gong, P., & Rida, I. (2021). Towards an efficient real-time kernel function stream clustering method via shared nearest-neighbor density for the iiot. Information Sciences, 566. Search in Google Scholar

eISSN:
2444-8656
Langue:
Anglais
Périodicité:
Volume Open
Sujets de la revue:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics