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Table 3 Random forest confusion matrix for date 1 of data collection (July 12)

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

 

Reference data

1 (%)

2 (%)

3 (%)

4 (%)

5 (%)

Predicted data

 1

76.4

22.8

0

0.8

0

 2

14.3

68.2

16.1

1.2

0.2

 3

0.8

19.2

65.3

14.7

0

 4

0

3.9

19.7

61.9

14.5

 5

0

0

0

100

0

Overall accuracy (%) = 68

  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 68%
  2. The diagonal elements are italicized to highlight the percentage of correctly classified field plots in terms of IDC score