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  "Title": "Fast Adaptive Spectral Clustering for Single and Multi-View Data",
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  "Author": "Christopher R John, David Watson",
  "Maintainer": "Christopher R John <chris.r.john86@gmail.com>",
  "Description": "A self-tuning spectral clustering method for single or\nmulti-view data. 'Spectrum' uses a new type of adaptive density\naware kernel that strengthens connections in the graph based on\ncommon nearest neighbours. It uses a tensor product graph data\nintegration and diffusion procedure to integrate different data\nsources and reduce noise. 'Spectrum' uses either the eigengap\nor multimodality gap heuristics to determine the number of\nclusters. The method is sufficiently flexible so that a wide\nrange of Gaussian and non-Gaussian structures can be clustered\nwith automatic selection of K.",
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      "page": "pca",
      "title": "pca: A pca function",
      "topics": [
        "pca"
      ]
    },
    {
      "page": "rbfkernel_b",
      "title": "rbfkernel_b: fast self-tuning kernel",
      "topics": [
        "rbfkernel_b"
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    },
    {
      "page": "sigma_finder",
      "title": "sigma_finder: heuristic to find sigma for the Ng kernel",
      "topics": [
        "sigma_finder"
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    },
    {
      "page": "Spectrum",
      "title": "Spectrum: Fast Adaptive Spectral Clustering for Single and Multi-view Data",
      "topics": [
        "Spectrum"
      ]
    },
    {
      "page": "spirals",
      "title": "Two spirals wrapped around one another",
      "topics": [
        "spirals"
      ]
    }
  ],
  "_rundeps": [
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    "ClusterR",
    "cpp11",
    "diptest",
    "farver",
    "ggplot2",
    "glue",
    "gmp",
    "gtable",
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    "labeling",
    "lifecycle",
    "R6",
    "RColorBrewer",
    "Rcpp",
    "RcppArmadillo",
    "RcppParallel",
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    "rlang",
    "S7",
    "scales",
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  "_vignettes": [
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      "source": "Spectrum_vignette.Rmd",
      "filename": "Spectrum_vignette.html",
      "title": "Spectrum",
      "author": "Christopher R John",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Contents",
        "1. Data types and requirements",
        "2. Quick start parameter settings",
        "3. Single-view clustering: Gaussian blobs",
        "4. Single-view clustering: Brain cancer RNA-seq",
        "5. Single-view clustering: Brain cancer RNA-seq clustering a range of K",
        "6. Multi-view clustering: Brain cancer multi-omics",
        "7. Multi-view clustering: Brain cancer multi-omics with missing data",
        "8. Single-view clustering: Non-Gaussian data, 3 circles",
        "9. Single-view clustering: Non-Gaussian data, spirals",
        "10. Ultra-fast single-view clustering: Gaussian blobs II",
        "11. Advanced operation: Ng spectral clustering",
        "12. Advanced operation: Customised data integration",
        "13. Parameter settings",
        "14. Code for heatmaps",
        "15. Closing comments",
        "16. References"
      ],
      "created": "2020-02-12 06:00:19",
      "modified": "2020-02-12 06:00:19",
      "commits": 1
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