{"url":"/dataset/three-view-synthetic-data","name":"Three-view Synthetic data","full_name":"Synthetic data","description_markdown":"10000 instances of three-view numerical data set with 4 clusters and 2 feature components are considered. The data points in each view are generated from a 2-component 2-variate Gaussian mixture model (GMM) where their mixing proportions $\\alpha_1^{(1)}=\\alpha_1^{(2)}=\\alpha_1^{(3)}=\\alpha_1^{(4)}=0.3$;  $\\alpha_2^{(1)}=\\alpha_2^{(2)}=\\alpha_2^{(3)}=\\alpha_2^{(4)}=0.15$; $\\alpha_3^{(1)}=\\alpha_3^{(2)}=\\alpha_3^{(3)}=\\alpha_3^{(4)}=0.15$  and $\\alpha_4^{(1)}=\\alpha_4^{(2)}=\\alpha_4^{(3)}=\\alpha_4^{(4)}=0.4$. The means  $\\mu_{ik}^{(1)}$ for the first view are $[-10 ~-5)]$,$[-9 ~ 11]$, $[0~ 6]$   and $[4~0]$;  The means  $\\mu_{ik}^{(2)}$ for the view 2 are $[-8 ~-12]$,$[-6 ~ -3]$, $[-2~ 7]$   and $[2~1]$; And the means  $\\mu_{ik}^{(3)}$ for the third view are $[-5 ~-10]$,$[-8 ~ -1]$, $[0~ 5]$   and $[5~-4]$. The covariance matrices for the three views are $\\Sigma_1^{(1)}=\\Sigma_1^{(2)}=\\Sigma_1^{(3)}=\\Sigma_1^{(4)}=\\left[ \\begin{array}{cc} 1 & 0\\\\0&1\\end{array}\\right]$; $\\Sigma_2^{(1)}=\\Sigma_2^{(2)}=\\Sigma_2^{(3)}=\\Sigma_2^{(4)}=3 \\left[ \\begin{array}{cc} 1 & 0\\\\0&1\\end{array}\\right]$;  $\\Sigma_3^{(1)}=\\Sigma_3^{(2)}=\\Sigma_3^{(3)}=\\Sigma_3^{(4)}=2 \\left[ \\begin{array}{cc} 1 & 0\\\\0&1\\end{array}\\right]$; and $\\Sigma_4^{(1)}=\\Sigma_4^{(2)}=\\Sigma_4^{(3)}=\\Sigma_4^{(4)}=0.5 \\left[ \\begin{array}{cc} 1 & 0\\\\0&1\\end{array}\\right]$. These $x_1^{(1)}$  and $x_2^{(1)}$  are the coordinates for the view 1,  $x_1^{(2)}$  and  $x_2^{(2)}$ are the coordinates for the view 2,  $x_1^{(3)}$ and $x_2^{(3)}$ are the coordinates for the view 3. While the original distribution of data points for cluster 1, cluster 2, cluster 3, and cluster 4 are 1514, 3046, 3903, and 1537, respectively.","description_withheld":null,"homepage":"https://patternkps.github.io","introduced_date":"2024-05-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/rectified-gaussian-kernel-multi-view-k-means","title":"Rectified Gaussian kernel multi-view k-means clustering","first_author":"Kristina P. Sinaga","url":null},"license":{"name":"MIT","url":"https://github.com/PatternKPS/RectifiedMVKM/blob/main/LICENSE"},"modalities":[],"tasks":[{"name":"Multiview Detection","url":"/task/multiview-detection","datasets_with_task":"/datasets/task/multiview-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Three-view Synthetic data"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}