Table 3 Performance evaluation of four employed classifiers in classifying movement categories.

From: Coming in handy: CeTI-Age — A comprehensive database of kinematic hand movements across the lifespan

 

Category A

Category B

Category C

KNNaccuracy

0.907 (0.028)

0.775 (0.025)

0.744 (0.028)

LDAaccuracy

0.914 (0.020)

0.760 (0.024)

0.659 (0.026)

RFaccuracy

0.944 (0.021)

0.844 (0.026)

0.793 (0.022)

SVCaccuracy

0.938 (0.023)

0.757 (0.025)

0.757 (0.023)

KNNF1

0.908 (0.027)

0.772 (0.026)

0.745 (0.028)

LDAF1

0.915 (0.019)

0.759 (0.025)

0.659 (0.026)

RFF1

0.944 (0.021)

0.841 (0.026)

0.792 (0.023)

SVCF1

0.938 (0.023)

0.798 (0.026)

0.758 (0.023)

  1. The table presents the mean accuracy and F1 scores used to evaluate the performance of the four employed classifiers: K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Random Forest (RF) and Support Vector Classifier (SVC). The classification task involves categorizing movements into three categories: A, B, and C. The values provided in the table represent the mean scores, accompanied by their corresponding standard deviations in in parentheses. Bold values indicate the highest scores within that category.
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