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Table 2 Classification performance of the k-NN and SVM classifiers in detecting compensation movements

From: Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms

 

Back-and-forth reaching

Side-to-side reaching

Up-and-down reaching

Average

k-NN

Precision

0.984

0.988

0.996

0.989

Recall

1.000

0.992

1.000

0.997

F1-score

0.992

0.990

0.998

0.993

SVM

Precision

0.988

0.996

0.996

0.993

Recall

1.000

0.979

1.000

0.993

F1-score

0.994

0.987

0.998

0.993

  1. k-NN = k-nearest neighbor, SVM = support vector machine