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Table 4 Random forest confusion matrix for date 2 of data collection (August 1)

From: Soybean iron deficiency chlorosis high-throughput phenotyping using an unmanned aircraft system

 

Reference data

1 (%)

2 (%)

3 (%)

4 (%)

5 (%)

Predicted data

 1

85.1

14.9

0

0

0

 2

10.4

79.6

9.3

0.5

0.2

 3

0.2

13

74

12

0.8

 4

0

0.6

9.9

73.6

15.9

 5

0

0

3.1

18.4

78.5

Overall accuracy (%) = 77

  1. The % green, % yellow, and % brown pixels from each of the research plots were used as features in a random forest model. This confusion matrix shows how well the random forest model predicted the iron deficiency chlorosis (IDC) score from ground-based reference data where each plot was rated on a one through five scale. The overall accuracy was 77%
  2. The diagonal elements are italicized to highlight the percentage of correctly classified field plots in terms of IDC score