February 11, 2018 Dataset Open Access

Koncar, Philipp

Dublin Core Export

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  <dc:creator>Koncar, Philipp</dc:creator>
  <dc:date>2018-02-11</dc:date>
  <dc:description>This synthetically generated dataset can be used to evaluate outlier detection algorithms. It has 10 attributes and 1000 observations, of which 100 are labeled as outliers. Two-dimensional combinations of attributes form differently shaped clusters.


	Attribute 0 &amp; Attribute 1: Two circular clusters
	Attribute 2 &amp; Attribute 3: Two banana shaped clusters
	Attribute 4 &amp; Attribute 5: Three point clouds
	Attribute 6 &amp; Attribute 7: Two point clouds with variances
	Attribute 8 &amp; Attribute 9: Three anisotropic shaped clusters. 


The "outlier" 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).</dc:description>
  <dc:identifier>https://zenodo.org/record/1171077</dc:identifier>
  <dc:identifier>10.5281/zenodo.1171077</dc:identifier>
  <dc:identifier>oai:zenodo.org:1171077</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.1171076</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>outlier detection</dc:subject>
  <dc:subject>synthetic</dc:subject>
  <dc:title>Synthetic Dataset for Outlier Detection</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>