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Table 3 Resubstitution error and confusion matrix for Random Forest (RF)-100 model

From: Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation

(a) Resubstitution error matrix for 2014

Land-use type

Agriculture land

Built-up land

Wasteland

Waterbody

Agriculture land

66

0

2

0

Built-up land

0

89

0

1

Wasteland

0

0

309

0

Waterbody

1

0

1

102

Training Overall accuracy = 0.99

(b) Confusion matrix for 2014

Land-use type

Agriculture land

Built-up land

Wasteland

Waterbody

Agriculture land

16

0

14

2

Built-up land

1

22

8

9

Wasteland

6

2

118

7

Waterbody

5

2

10

29

Testing (Validation) accuracy = 0.74

(c) Resubstitution error matrix for 2020

Land-use type

Agriculture land

Built-up land

Wasteland

Waterbody

Agriculture land

68

0

1

0

Built-up land

0

92

0

1

Wasteland

0

0

312

0

Waterbody

0

0

3

103

Training Overall accuracy = 0.99

(d) Confusion matrix for 2020

Land-use type

Agriculture land

Built-up land

Wasteland

Waterbody

Agriculture land

16

2

11

2

Built-up land

1

31

3

2

Wasteland

2

3

121

4

Waterbody

1

0

19

23

Testing (Validation) accuracy = 0.79