Quantum Machine Learning: An Effective Approach to High-dimensional Learning

Das, Jeevan Kumar A; Malhotra, Meenakshi

doi:10.1109/csitss57437.2022.10026399

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B Application Of Qml On Cardiac Datasets2

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Cited by 2 publications

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“…They include Quantum Random Forest Classifier (QRFC), Quantum K-Nearest Neighbors (QKNN), QSVM, Bagging-QSVC, QNN, instancebased QML, Quantum K-means(Q K-means), and Hybrid Quantum Machine Learning Perceptron (HQMLP). Techniques implemented on the UCI repository are described in [28] , [29], [30], [31], and [32]. The researchers in [28] QRFC using the Euclidean distance metric.…”

Section: B Application Of Qml On Cardiac Datasetsmentioning

confidence: 99%

See 1 more Smart Citation

QuCardio: Application of Quantum Machine Learning for Detection of Cardiovascular Diseases

Prabhu,

Gupta,

Prabhu

et al. 2023

IEEE Access

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Section: B Application Of Qml On Cardiac Datasetsmentioning

confidence: 99%

“…The authors in [30] observed that the Bagging QSVC outperformed QSVC, QNN, and QVC. In [31] compared an SVM and a QSVM on the dataset and observed that the QSVM showed better accuracy with lower time complexity. The method uses an optimized QSVM and a hybrid quantum multi-layer perceptron.…”

Section: B Application Of Qml On Cardiac Datasetsmentioning

confidence: 99%