[Retracted] Machine Learning Approaches for Developing Land Cover Mapping

Table 4

Precision, recall, and F1-score for the original and the best reduced dataset using RF classifier.

Class	Precision		Recall		F1-score
	Original dataset	Reduced (CFS)	Original dataset	Reduced (CFS)	Original dataset	Reduced (CFS)
Concrete	0.875	0.878	0.828	0.849	0.851	0.863
Shadow	0.875	0.930	0.933	0.889	0.903	0.909
Tree	0.820	0.880	0.920	0.910	0.868	0.895
Asphalt	0.909	0.820	0.889	0.911	0.899	0.863
Building	0.810	0.825	0.876	0.876	0.842	0.850
Grass	0.892	0.900	0.795	0.867	0.841	0.883
Pool	1.00	1.00	0.714	0.786	0.833	0.880
Car	0.818	0.895	0.857	0.810	0.837	0.850
Soil	0.813	0.789	0.650	0.750	0.717	0.769
W. avg.	0.857	0.872	0.854	0.870	0.829	0.870