Skip to main content

Table 2 The performances of KNN classifiers based on different kind of features

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

Feature set Feature number Accuracy Sensitivity Specificity Training time (s) Prediction speed (obs/s)
FO 14 98.60% 98.85% 97.63% 2.2781 18,000
GLCM 36 99.20% 99.48% 97.96% 5.3947 6500
GGCM 15 99.20% 99.42% 98.47% 2.7419 14,000
FO_GLCM 50 99.60% 99.90% 98.65% 7.2376 5100
FO_GGCM 29 99.60% 99.66% 99.25% 5.3189 9400
GLCM_GGCM 51 99.60% 99.76% 99.10% 7.354 4800
FO_GLCM_GGCM 65 99.80% 99.19% 99.92% 8.3886 4300