Machine learning driven non-invasive approach of water content estimation in living plant leaves using terahertz waves

Table 11 Classification performance of all classifiers by applying tenfold validation using proposed algorithms with selected features

Feature types and feature selection methods	Computation time (s)
Feature types and feature selection methods	SVM	KNN	Decision tree
Coffee leaf
Extracted features	0.7282	0.5309	0.4021
Selected features
SFS	0.5706	0.4123	0.3371
SBS	0.6456	0.4240	0.3202
Relief-F	0.6252	0.4842	0.3582
Baby spinach leaf
Extracted features	0.8975	0.4265	0.4053
Selected features
SFS	0.6062	0.4128	0.1071
SBS	0.4259	0.3576	0.3247
Relief-F	0.4485	0.3875	0.3490
Peashoot leaf
Extracted features	0.6825	0.4405	0.4196
Selected features
SFS	0.4699	0.3404	0.3343
SBS	0.6504	0.1734	0.3149
Relief-F	0.5088	0.3766	0.3759

ISSN: 1746-4811