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. Author manuscript; available in PMC: 2021 Oct 13.
Published in final edited form as: Proc ACM Interact Mob Wearable Ubiquitous Technol. 2020 Mar 18;4(1):4. doi: 10.1145/3380987

Table 3.

Shows the performance of the Logistic Regression model for various choices of windowing and labeling approaches.

# of Windows Logistic Regression
Windowing Labeling Labeled as ‘High’ Labeled as ‘Low’ F1 Precision Recall
Win-Loc Easily-Allowed 290 376 51.67 55.34 51.79
Win-Loc-Act Easily-Allowed 658 705 63.07 62.26 65.19
Win-Loc Easily-Fairly-Allowed 373 293 67.98 63.95 74.31
Win-Loc-Act Easily-Fairly-Allowed 808 555 74.3 70.27 79.82