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Table 10 Classification result on each extracted set of features for grapes rot leave disease

From: A probabilistic segmentation and entropy-rank correlation-based feature selection approach for the recognition of fruit diseases

Method Features Performance measures
  SLBP Harlick Color Sen (%) Spec (%) Accuracy (%)
DT    89.35 91.0 89.4
     86.40 86.6 86.4
    93.95 92.5 94.1
QSVM    89.45 85.1 89.4
     89.45 86.6 89.4
    94.55 90.6 94.9
CSVM    90.10 91.0 90.2
     87.90 86.6 87.9
    94.55 90.6 94.9
QDA    90.30 80.6 90.2
     88.0 80.6 87.9
    93.95 92.5 94.1
Fine KNN    88.70 83.6 88.6
     87.15 85.1 87.1
    95.50 92.5 95.8
WKNN    91.75 86.6 91.7
     82.60 82.4 82.6
    94.70 92.5 94.9
EBT    90.85 86.6 90.9
     89.45 86.6 89.4
    95.30 90.6 95.8
ESDA    89.45 85.1 89.4
     87.90 82.1 87.9
    93.50 92.5 94.1
Multi-class SVM    93.15 92.5 93.2
     91.0 85.1 90.9
    95.30 90.6 95.8
  1. The bold values indicate best results