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Synthetic Dataset for Outlier Detection

Koncar, Philipp


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{
  "description": "<p>This synthetically generated dataset can be used to evaluate outlier detection algorithms. It has 10 attributes and 1000 observations, of which 100 are&nbsp;labeled as outliers. Two-dimensional combinations of attributes form differently shaped clusters.</p>\n\n<ul>\n\t<li>Attribute 0 &amp; Attribute&nbsp;1: Two circular clusters</li>\n\t<li>Attribute&nbsp;2 &amp; Attribute&nbsp;3: Two banana shaped clusters</li>\n\t<li>Attribute&nbsp;4 &amp; Attribute&nbsp;5: Three point clouds</li>\n\t<li>Attribute&nbsp;6 &amp; Attribute&nbsp;7: Two point clouds with variances</li>\n\t<li>Attribute&nbsp;8 &amp; Attribute&nbsp;9: Three anisotropic shaped clusters.&nbsp;</li>\n</ul>\n\n<p>The &quot;outlier&quot; column states whether an observation is an outlier or not. Additionally, the .zip file contains 10 stratified randomized train test splits (70% train, 30% test).</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "", 
      "@type": "Person", 
      "name": "Koncar, Philipp"
    }
  ], 
  "url": "https://zenodo.org/record/1171077", 
  "datePublished": "2018-02-11", 
  "version": "1.0", 
  "keywords": [
    "outlier detection", 
    "synthetic"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/b0c11d63-67e4-494c-b9ad-46819b7cbe27/synthetic.zip", 
      "@type": "DataDownload", 
      "fileFormat": "zip"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.1171077", 
  "@id": "https://doi.org/10.5281/zenodo.1171077", 
  "@type": "Dataset", 
  "name": "Synthetic Dataset for Outlier Detection"
}
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