Kernel Clustering

Kernel Clustering is a clustering method that belongs to the class of kernel-based learning techniques, distinguished by its use of a kernel function to map input data into a higher-dimensional feature space where nonlinear cluster structures can be identified more effectively.

404

Publications

21.4K

Citations

1K

Authors

450

Institutions

Publications per year

2017–2026

179

Variants

Kernel-based Clustering

Authors

1K

  1. XL
    Xinwang Liu

    National University of Defense Technology, China

    25 publications · 1.7K citations

    20

    h-index

  2. JA
    Johan A. K. Suykens

    KU Leuven, Belgium

    20 publications · 665 citations

    16

    h-index

  3. EZ
    En Zhu

    National University of Defense Technology, China

    15 publications · 1.2K citations

    15

    h-index

  4. RL
    Rocco Langone

    KU Leuven, Belgium

    14 publications · 544 citations

    12

    h-index

  5. JY
    Jianping Yin

    National University of Defense Technology, China

    10 publications · 935 citations

    10

    h-index

1–5 of 1K

Venues

  1. Pattern Recognition

    15 publications · 1.5K citations

    14

    h-index

  2. Neurocomputing

    14 publications · 556 citations

    13

    h-index

  3. Expert Systems with Applications

    11 publications · 537 citations

    11

    h-index

  4. IEEE Transactions on Fuzzy Systems

    TFS · 11 publications · 1.4K citations

    11

    h-index

  5. Information Sciences

    10 publications · 544 citations

    10

    h-index

1–5