Table 4 Summarized comparison among variants of QSVM algorithms.

From: Quantum computing and machine learning for Arabic language sentiment classification in social media

Year

Algorithm

Approach

State preparation scheme

Kernel function

Speed-up

Complexity

Performance

Implementation

2020

Improved QSVM36

Hamiltonian simulation and matrix-inversion based QRAM

Nonlinear

Exponential

Polylogarithmic

Accuracy: 0.9514

Qiskit Python Library

 

2019

QSVM37

HHL algorithm based

Linear mapping

Linear

Exponential

–

Accuracy: 99.5% (OCR), 98% (Iris)

Qiskit Python Library, pyQuil

2020

HVQ-SVM38

Hybrid variables based QPCA and QSVT

Nonlinear

Exponential

Polylogarithmic

N.I

N.I

 

2023

QSLS-SVM39

Hybrid variables approach and classical matrix inversion based QPCA and QSVT

Nonlinear

Exponential

Polynomial

N.I

N.I

 
  1. QSVM quantum support vector machine, HVQ-SVM hybrid variable quantum support vector machine, QSLS-SVM quantum sparse least square support vector machine, QRAM quantum random access memory, QPCA quantum principal component analysis, QSVT quantum singular value threshold, OCR optical character recognition, N.I. no implementation (either no implementation or details not given).
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