Quantum decision tree classifier View Full Text


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Article Info

DATE

2013-11-19

AUTHORS

Songfeng Lu, Samuel L. Braunstein

ABSTRACT

We study the quantum version of a decision tree classifier to fill the gap between quantum computation and machine learning. The quantum entropy impurity criterion which is used to determine which node should be split is presented in the paper. By using the quantum fidelity measure between two quantum states, we cluster the training data into subclasses so that the quantum decision tree can manipulate quantum states. We also propose algorithms constructing the quantum decision tree and searching for a target class over the tree for a new quantum object. More... »

PAGES

757-770

References to SciGraph publications

  • 2001-05-09. Pattern Recognition with Quantum Neural Networks in ADVANCES IN PATTERN RECOGNITION — ICAPR 2001
  • 2006. Machine Learning in a Quantum World in ADVANCES IN ARTIFICIAL INTELLIGENCE
  • 2012-11-21. Quantum adiabatic machine learning in QUANTUM INFORMATION PROCESSING
  • 2012-08-31. Quantum speed-up for unsupervised learning in MACHINE LEARNING
  • 1986-03. Induction of decision trees in MACHINE LEARNING
  • 2011-04-30. A quantum production model in QUANTUM INFORMATION PROCESSING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11128-013-0687-5

    DOI

    http://dx.doi.org/10.1007/s11128-013-0687-5

    DIMENSIONS

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