Table 3 Comparison of our methodology to simpler alternative methods.

From: Mosquito species identification using convolutional neural networks with a multitiered ensemble model for novel species detection

 

McNemar’s Test, χ21

Macro F1-score

Macro unknown recall/sensitivity

Macro unknown precision

Full methods

 

86.24 ± 2.48%

94.09 ± 2.42%

79.66 ± 3.24%

Soft voting of all T2 components

χ21 = 332 a

p < 0.00001

86.87 ± 3.11%

88.55 ± 3.58%

85.36 ± 3.93%

T2–closed-set Random Forest

χ21 = 920

p < 0.00001

82.80 ± 3.84%

83.79 ± 4.86%

81.97 ± 4.23%

T2 – closed-set SVM

χ21 = 1120

p < 0.00001

82.68 ± 4.51%

82.93 ± 5.68%

82.58 ± 4.60%

T2–closed-set WDNN

χ21 = 905

p < 0.00001

81.87 ± 4.53%

87.34 ± 5.96%

77.11 ± 3.93%

Softmax with a threshold

χ21 = 12,151

p < 0.00001

72.38 ± 4.43%

61.81 ± 4.31%

87.43 ± 5.47%

Open-set re-mapped

χ21 = 24,656

p < 0.00001

72.72 ± 4.28%

58.03 ± 5.52%

98.02 ± 1.98%

ODIN

χ21 = 6414

p < 0.00001

49.58 ± 26.02%

68.87 ± 42.70%

82.02 ± 5.77%

  1. aA high chi-squared (χ21) value dictates a low p-value, which indicates a statistically significant difference with the full methods.