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. 2021 Jun 22;2021:5592323. doi: 10.1155/2021/5592323

Table 2.

Classification accuracies (%) achieved using 40 selected bands in Indian Pines with KNN classifier.

Class Algorithm
Accuracy (%)
MVPCA WaLuDi DBSCAN FDPC LP ISSC TLS
Alfalfa 66.8 54.6 50.5 39.2 33.7 34.2 45.4
Corn-notill 60.5 71.3 69.6 71 64.3 75.8 73.7
Corn-mintill 41.5 57.4 60 66.8 48.7 65.2 66.8
Corn 48.4 57.4 57.7 58.3 53.8 53.1 60.1
Grass-pasture 82.6 88.7 86.2 85 88.4 82.1 84.4
Grass-trees 93.1 94.5 95 94.3 93.3 96.7 96
Grass-pasture-mowed 45.2 44.8 42.1 37.3 71.7 92 45.2
Hay-windrowed 97.6 96.3 96.6 95.8 98.1 96.7 96.6
Oats 29.8 24.2 27 24.4 38.3 61.2 29.7
Soybean-notill 59.5 76.2 73.7 68.3 67.2 79.4 75.7
Soybean-mintill 77.4 79.3 81.5 82.6 82.9 82.5 84.2
Soybean-clean 43.1 69.6 71 72.2 58.9 83.3 72
Wheat 93 97.7 98.4 98.1 96.2 96.2 95.4
Woods 93.6 94.4 93.3 93.5 94.6 96.8 95.8
Buildings-grass-trees-drives 42.7 52.7 51.9 50.4 54.9 53.6 55.1
Stone-steel-towers 94.9 76.3 78.4 83.6 69.7 80.9 82.4

AA 66.8 70.9 70.6 70 69.7 76.9 72.4
OA 74 77.8 76.2 77.1 75.3 79.7 80.8
Variance 515.4 421.4 421.1 487.7 410.0 326.2 399.3