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

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

Feature types and feature selection methodsComputation time (s)
SVMKNNDecision tree
Coffee leaf   
 Extracted features0.72820.53090.4021
 Selected features   
  SFS0.57060.41230.3371
  SBS0.64560.42400.3202
  Relief-F0.62520.48420.3582
 Baby spinach leaf   
 Extracted features0.89750.42650.4053
 Selected features   
  SFS0.60620.41280.1071
  SBS0.42590.35760.3247
  Relief-F0.44850.38750.3490
Peashoot leaf   
 Extracted features0.68250.44050.4196
 Selected features   
  SFS0.46990.34040.3343
  SBS0.65040.17340.3149
  Relief-F0.50880.37660.3759