. Author manuscript; available in PMC: 2022 Dec 19.

Published in final edited form as: Proc ACM Interact Mob Wearable Ubiquitous Technol. 2020 Mar 18;4(1):23. doi: 10.1145/3381001

Table 4.

F1 score among eight machine learning algorithms using feature selection. The support vector classifier with RBF kernel achieves the highest F1 score of 0.793.

Algorithm	F1 score
KNN	0.756
Linear SVC	0.644
SVC (RBF kernel)	0.793
Gaussian Naive Bayes	0.654
Bernoulli Naive Bayes	0.736
Logistic Regression	0.717
Random Forest	0.672
XGBoost	0.641