How to visualize high-dimensional data

被引:0
|
作者
Mrowka, Ralf [1 ]
Schmauder, Ralf [2 ]
机构
[1] Friedrich Schiller Univ, Univ Klinikum Jena, KIM 3, Expt Nephrol, Nonnenplan 4, Jena, Thuringia, Germany
[2] Friedrich Schiller Univ, Univ Klinikum Jena, Inst Physiol 2, Kollegiengasse 9, Jena, Thuringia, Germany
关键词
dimension reduction; principal component analysis; T-SNE; UMAP;
D O I
10.1111/apha.14219
中图分类号
Q4 [生理学];
学科分类号
071003 ;
摘要
引用
收藏
页数:4
相关论文
共 50 条
  • [41] Procrustes Analysis for High-Dimensional Data
    Andreella, Angela
    Finos, Livio
    PSYCHOMETRIKA, 2022, 87 (04) : 1422 - 1438
  • [42] Adaptive Testing for High-Dimensional Data
    Zhang, Yangfan
    Wang, Runmin
    Shao, Xiaofeng
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2025,
  • [43] Clustering in high-dimensional data spaces
    Murtagh, FD
    STATISTICAL CHALLENGES IN ASTRONOMY, 2003, : 279 - 292
  • [44] Compressive Clustering of High-dimensional Data
    Ruta, Andrzej
    Porikli, Fatih
    2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 1, 2012, : 380 - 385
  • [45] Learning to visualise high-dimensional data
    Ahmad, K
    Vrusias, B
    EIGHTH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION, PROCEEDINGS, 2004, : 507 - 512
  • [46] Bump hunting in high-dimensional data
    Friedman J.H.
    Fisher N.I.
    Statistics and Computing, 1999, 9 (2) : 123 - 143
  • [47] REGULARISED MANOVA FOR HIGH-DIMENSIONAL DATA
    Ullah, Insha
    Jones, Beatrix
    AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, 2015, 57 (03) : 377 - 389
  • [48] Semisupervised visualization of high-dimensional data
    Kouropteva O.
    Okun O.
    Pietikäinen M.
    Pattern Recognition and Image Analysis, 2007, 17 (04) : 612 - 620
  • [49] Dynamics of ICA for high-dimensional data
    Basalyga, G
    Rattray, M
    ARTIFICIAL NEURAL NETWORKS - ICANN 2002, 2002, 2415 : 1112 - 1118
  • [50] Polynomial whitening for high-dimensional data
    Jonathan Gillard
    Emily O’Riordan
    Anatoly Zhigljavsky
    Computational Statistics, 2023, 38 : 1427 - 1461