Performance Evaluation of CMOS Annealing with Support Vector Machine
2024
Online
report
In this paper, support vector machine (SVM) performance was assessed utilizing a quantum-inspired complementary metal-oxide semiconductor (CMOS) annealer. The primary focus during performance evaluation was the accuracy rate in binary classification problems. A comparative analysis was conducted between SVM running on a CPU (classical computation) and executed on a quantum-inspired annealer. The performance outcome was evaluated using a CMOS annealing machine, thereby obtaining an accuracy rate of 93.7% for linearly separable problems, 92.7% for non-linearly separable problem 1, and 97.6% for non-linearly separable problem 2. These results reveal that a CMOS annealing machine can achieve an accuracy rate that closely rivals that of classical computation.
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Performance Evaluation of CMOS Annealing with Support Vector Machine
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Autor/in / Beteiligte Person: | Fukuhara, Ryoga ; Morishita, Makoto ; Katagiri, Takahiro ; Kawai, Masatoshi ; Nagai, Toru ; Hoshino, Tetsuya |
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Veröffentlichung: | 2024 |
Medientyp: | report |
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