Quantum decision tree classifier

Songfeng Lu; Samuel Leon Braunstein

doi:10.1007/s11128-013-0687-5

Quantum decision tree classifier

Songfeng Lu, Samuel Leon Braunstein

Computer Science

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	757-770
Number of pages	14
Journal	Quantum Information Processing
Volume	13
Issue number	3
DOIs	https://doi.org/10.1007/s11128-013-0687-5
Publication status	Published - Mar 2014

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10.1007/s11128-013-0687-5

Cite this

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title = "Quantum decision tree classifier",

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.",

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