Dataset Open Access
Koncar, Philipp
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <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 & Attribute 1: Two circular clusters Attribute 2 & Attribute 3: Two banana shaped clusters Attribute 4 & Attribute 5: Three point clouds Attribute 6 & Attribute 7: Two point clouds with variances Attribute 8 & 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>https://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>
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