February 11, 2018 Dataset Open Access

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>", 
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    "title": "Synthetic Dataset for Outlier Detection", 
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