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

Blondel, Mathieu; Pedregosa, Fabian


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{
  "description": "<p>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/.</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "NTT", 
      "@type": "Person", 
      "name": "Blondel, Mathieu"
    }, 
    {
      "affiliation": "INRIA", 
      "@type": "Person", 
      "name": "Pedregosa, Fabian"
    }
  ], 
  "url": "https://zenodo.org/record/200504", 
  "datePublished": "2016-12-13", 
  "keywords": [
    "machine learning", 
    "Python", 
    "supervised learning"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.200504", 
  "@id": "https://doi.org/10.5281/zenodo.200504", 
  "@type": "SoftwareSourceCode", 
  "name": "Lightning: large-scale linear classification, regression and ranking in Python"
}
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