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Table 4 The performances of SVM classifiers based on different kinds of features

From: A study of hepatic fibrosis staging methods using diffraction enhanced imaging

Feature Set Accuracy Sensitivity Specificity Training time (s) Prediction speed (obj/s)
FO 98.41% 98.68% 97.39% 58.413 12,000
GLCM 99.49% 99.73% 98.56% 93.538 6900
GGCM 99.31% 99.35% 99.15% 61.643 11,000
FO_GLCM 99.73% 98.85% 99.25% 40.354 13,000
FO_ GGCM 99.68% 99.75% 99.40% 45.398 13,000
GLCM_GGCM 99.73% 99.82% 99.37% 41.978 12,000
FO_GLCM_GGCM 99.81% 99.84% 99.69% 48.903 10,000