January 31, 2019 Software Open Access

Pradeep Reddy Raamana; Kevin Le

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  <dc:creator>Pradeep Reddy Raamana</dc:creator>
  <dc:creator>Kevin Le</dc:creator>
  <dc:date>2019-01-31</dc:date>
  <dc:description>
Good news: neuropredict can handle missing data now (that are encoded with numpy.NaN). This is done respecting the cross-validation splits without any data leakage.
Few other useful utilities
</dc:description>
  <dc:identifier>https://zenodo.org/record/2554478</dc:identifier>
  <dc:identifier>10.5281/zenodo.2554478</dc:identifier>
  <dc:identifier>oai:zenodo.org:2554478</dc:identifier>
  <dc:relation>url:https://github.com/raamana/neuropredict/tree/0.5</dc:relation>
  <dc:relation>doi:10.5281/zenodo.997355</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:title>raamana/neuropredict: Support for Missing data</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>software</dc:type>
</oai_dc:dc>