Quantum decision tree classifier

被引：89

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

页码：757 / 770

页数：14

共 21 条

[1]

Aïmeur E, 2006, LECT NOTES ARTIF INT, V4013, P431

[2] Quantum speed-up for unsupervised learning [J].

Aimeur, Esma ;

Brassard, Gilles ;

Gambs, Sebastien .

MACHINE LEARNING, 2013, 90 (02) :261-287

[3]

[Anonymous], 1996, ARXIV

[4]

Bishop C., 2006, PATTERN RECOGN, DOI DOI 10.1117/1.2819119

[5]

Bonner R., 2002, Proceedings of the 3rd International Workshop on Quantum Computation and Learning (QCL'02), P106

[6] Complexity measures and decision tree complexity: a survey [J].

Buhrman, H ;

de Wolf, R .

THEORETICAL COMPUTER SCIENCE, 2002, 288 (01) :21-43

[7]

Ezhov A. A., 2001, Advances in Pattern Recognition - ICAPR 2001. Second International Conference. Proceedings (Lecture Notes in Computer Science Vol.2013), P60

[8]

Gambs S., 2008, ARXIVQUANTPH08090444

[9]

Grover L. K., 1996, Proceedings of the Twenty-Eighth Annual ACM Symposium on the Theory of Computing, P212, DOI 10.1145/237814.237866

[10] Quantum learning: asymptotically optimal classification of qubit states [J].

Guta, Madalin ;

Kotlowski, Wojciech .

NEW JOURNAL OF PHYSICS, 2010, 12

← 1 2 3 →