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Lightning: large-scale linear classification, regression and ranking in Python

Blondel, Mathieu; Pedregosa, Fabian


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  <dc:creator>Blondel, Mathieu</dc:creator>
  <dc:creator>Pedregosa, Fabian</dc:creator>
  <dc:date>2016-12-13</dc:date>
  <dc:description>Lightning is a Python library for large-scale machine learning. More specifically, the library focuses on linear models for classification, regression and ranking. Lightning is the first project to integrate scikit-learn-contrib, a repository of high-quality projects that follow the same API conventions as scikit-learn. Compared to scikit-learn, the main advantages of lightning are its scalability and its flexibility. Indeed, lightning implements cutting-edge optimization algorithms that allow to train models with millions of samples within seconds on commodity hardware. Furthermore, lightning can leverage prior knowledge thanks to so-called structured penalties, an area of research that has recently found applications in domains as diverse as biology, neuroimaging, finance or text processing. Lightning is available under the 3-clause BSD license at http://contrib.scikit-learn.org/lightning/.</dc:description>
  <dc:identifier>https://zenodo.org/record/200504</dc:identifier>
  <dc:identifier>10.5281/zenodo.200504</dc:identifier>
  <dc:identifier>oai:zenodo.org:200504</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>machine learning</dc:subject>
  <dc:subject>Python</dc:subject>
  <dc:subject>supervised learning</dc:subject>
  <dc:title>Lightning: large-scale linear classification, regression and ranking in Python</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>software</dc:type>
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