KFU. Card publication. Quantum Circuit for Random Forest Prediction

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

QUANTUM CIRCUIT FOR RANDOM FOREST PREDICTION

Form of presentation

Articles in international journals and collections

Year of publication

2023

Язык

английский

Authors, employees of KFU

Zinnatullin Ilnar Gumarovich, author

Safina Liliya Ilkhamovna, author

Khadiev Kamil Ravilevich, author

Khadieva Aliya Ikhsanovna, author

Bibliographic description in the original language

Safina L, Khadiev K, Zinnatullin I, Khadieva A., Quantum Circuit for Random Forest Prediction//Russian Microelectronics. - 2023. - Vol.52, Is.Suppl 1. - P.S384-S389.

Annotation

In this work, we present a quantum circuit for a binary classification prediction algorithm using a random forest model. The quantum prediction algorithm is presented in our previous works. We construct a circuit and implement it using qiskit tools (python module for quantum programming). One of our goals is reducing the number of basic quantum gates (elementary gates). The set of basic quantum gates which we use in this work consists of single-qubit gates and a controlled NOT gate. The number of CNOT gates in our circuit is estimated by, when trivial circuit decomposition techniques give CNOT gates, where is the number of trees in a random forest model, is a tree height and is the length of attributes of an input object. The prediction process returns an index of the corresponding class for the input.

Keywords

quantum algorithms, machine learning, random forest, quantum programming

The name of the journal

Russian Microelectronics

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188519881&doi=10.1134%2fS1063739723600619&partnerID=40&md5=713c48228f40a4160a7a36dd99db25a7

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=297972&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Zinnatullin Ilnar Gumarovich	ru_RU
dc.contributor.author	Safina Liliya Ilkhamovna	ru_RU
dc.contributor.author	Khadiev Kamil Ravilevich	ru_RU
dc.contributor.author	Khadieva Aliya Ikhsanovna	ru_RU
dc.date.accessioned	2023-01-01T00:00:00Z	ru_RU
dc.date.available	2023-01-01T00:00:00Z	ru_RU
dc.date.issued	2023	ru_RU
dc.identifier.citation	Safina L, Khadiev K, Zinnatullin I, Khadieva A., Quantum Circuit for Random Forest Prediction//Russian Microelectronics. - 2023. - Vol.52, Is.Suppl 1. - P.S384-S389.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=297972&p_lang=2	ru_RU
dc.description.abstract	Russian Microelectronics	ru_RU
dc.description.abstract	In this work, we present a quantum circuit for a binary classification prediction algorithm using a random forest model. The quantum prediction algorithm is presented in our previous works. We construct a circuit and implement it using qiskit tools (python module for quantum programming). One of our goals is reducing the number of basic quantum gates (elementary gates). The set of basic quantum gates which we use in this work consists of single-qubit gates and a controlled NOT gate. The number of CNOT gates in our circuit is estimated by, when trivial circuit decomposition techniques give CNOT gates, where is the number of trees in a random forest model, is a tree height and is the length of attributes of an input object. The prediction process returns an index of the corresponding class for the input.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	quantum algorithms	ru_RU
dc.subject	machine learning	ru_RU
dc.subject	random forest	ru_RU
dc.subject	quantum programming	ru_RU
dc.title	Quantum Circuit for Random Forest Prediction	ru_RU
dc.type	Articles in international journals and collections	ru_RU