BMC Bioinformatics

Table 10 Test set accuracy (%) of the machine learning models

From: A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application

SBERT before SMOTE			SBERT after SMOTE
	APC	ATM	APC	ATM
Random forest	66.6 ± 0.36	73.3 ± 0.18	66.5 ± 0.33	73.3 ± 0.16
XGBoost	67.1 ± 0.40	73.2 ± 0.20	67.1 ± 0.40	73.3 ± 0.20
LightGBM	67.4 ± 0.41	73.3 ± 0.18	67.4 ± 0.41	73.3 ± 0.18
CNN	67.2 ± 0.42	74. ± 0.12	66.8 ± 0.42	70.71 ± 0.17

SimCSE before SMOTE			SimCSE after SMOTE
	APC	ATM	APC	ATM
Random forest	66.5 ± 0.37	73.7 ± 0.12	66.6 ± 0.35	73.6 ± 0.14
XGBoost	67.1 ± 0.41	73.9 ± 0.12	67.1 ± 0.41	75. ± 0.12
LightGBM	67.4 ± 0.41	74.1 ± 0.20	67.4 ± 0.41	74.1 ± 0.20
CNN	67.4± 0.47	75. ± 0.12	67.3 ± 0.46	73.3 ± 0.14

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ISSN: 1471-2105

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