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Table 1 Performances of KNN with Euclidean, Cosine, and Minkowski distance metrics

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

Distance metric

Accuracy

Sensitivity

Specificity

Training time(s)

Prediction speed (obs/s)

Euclidean

99.21%

99.38%

98.54%

2.4916

18,000

Cosine

99.13%

99.22%

98.80%

2.503

18,000

Minkowski

99.23%

99.39%

98.54%

58.548

570