Dataset Open Access

Synthetic Dataset for Outlier Detection

Koncar, Philipp


MARC21 XML Export

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    <subfield code="a">&lt;p&gt;This synthetically generated dataset can be used to evaluate outlier detection algorithms. It has 10 attributes and 1000 observations, of which 100 are&amp;nbsp;labeled as outliers. Two-dimensional combinations of attributes form differently shaped clusters.&lt;/p&gt;

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

&lt;p&gt;The &amp;quot;outlier&amp;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).&lt;/p&gt;</subfield>
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