Quantum decision tree classifier

被引：75
|
作者：
Lu, Songfeng [1 ]
Braunstein, Samuel L. [2 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China
[2] Univ York, Dept Comp Sci, York YO10 5GH, N Yorkshire, England
来源：
QUANTUM INFORMATION PROCESSING | 2014年 / 13卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Quantum information processing; Quantum entropy; Quantum decision tree; Quantum classification; Machine learning;
D O I：
10.1007/s11128-013-0687-5
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
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.
引用
收藏
页码：757 / 770
页数：14
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