Quantum decision tree classifier

被引:0
|
作者
Songfeng Lu
Samuel L. Braunstein
机构
[1] Huazhong University of Science and Technology,School of Computer Science and Technology
[2] University of York,Department of Computer Science
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关键词
Quantum information processing; Quantum entropy; Quantum decision tree; Quantum classification; Machine learning;
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学科分类号
摘要
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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页码:757 / 770
页数:13
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