Learning with Ensembles of Randomized Trees : New Insights

  title={Learning with Ensembles of Randomized Trees : New Insights},
  author={Vincent Pisetta and Pierre-Emmanuel Jouve and D. Zighed},
Ensembles of randomized trees such as Random Forests are among the most popular tools used in machine learning and data mining. Such algorithms work by introducing randomness in the induction of several decision trees before employing a voting scheme to give a prediction for unseen instances. In this paper, randomized trees ensembles are studied in the point of view of the basis functions they induce. We point out a connection with kernel target alignment, a measure of kernel quality, which… Expand
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Random Forests
  • L. Breiman
  • Mathematics, Computer Science
  • Machine Learning
  • 2004
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