Ensemble Averaging

Ensemble Averaging

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Description

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In machine learning, particularly in the creation of artificial neural networks, ensemble averaging is the process of creating multiple models and combining them to produce a desired output, as opposed to creating just one model. Frequently an ensemble of models performs better than any individual model, because the various errors of the models "average out." Ensemble averaging is one of the simplest types of committee machines. Along with boosting, it is one of the two major types of static committee machines. In contrast to standard network design in which many networks are generated but only one is kept, ensemble averaging keeps the less satisfactory networks around, but with less weight.show more

Product details

  • Paperback | 56 pages
  • 152 x 229 x 3mm | 95g
  • Plaispublishing
  • United States
  • English
  • black & white illustrations
  • 6136260743
  • 9786136260747