Table 3.

Performance of the classifiers (average F₁ score and accuracy in 10-fold cross-validation).

Criterion	Deep learninga, mean (SD)		Support vector machinesa, mean (SD)		Random forestsa, mean (SD)
	F1 score	Accuracy	F1 score	Accuracy	F1 score	Accuracy
1	0.851 (0.005)	0.740 (0.008)	0.903 (0.032)	0.842 (0.045)	0.950 (0.015)	0.924 (0.019)
2	0.000 (0.000)	0.638 (0.003)	0.802 (0.044)	0.828 (0.018)	0.915 (0.005)	0.943 (0.006)
3	0.000 (0.000)	0.865 (0.009)	0.761 (0.038)	0.917 (0.011)	0.745 (0.088)	0.944 (0.018)
4	0.882 (0.001)	0.789 (0.002)	0.903 (0.042)	0.833 (0.068)	0.959 (0.017)	0.936 (0.022)
5	0.551 (0.249)	0.486 (0.051)	0.787 (0.034)	0.721 (0.051)	0.921 (0.022)	0.920 (0.020)
6	0.867 (0.002)	0.765 (0.004)	0.912 (0.006)	0.852 (0.010)	0.964 (0.002)	0.943 (0.004)
7	0.000 (0.000)	0.840 (0.008)	0.801 (0.029)	0.924 (0.006)	0.764 (0.057)	0.936 (0.004)

^aThe classifier with the highest F1-score is italicized for each criterion.