Table 3. Classification Performance vs. RMSE in Estimated DLMO.

A comparison of classification accuracy (predicting if a timepoint falls before or after DLMO) to the resulting RMSE between estimated DLMO, calculated based on the switch in classification, and the experimentally measured DLMO for different classification models.

Model	Full Dataset		Actigraphy Dataset
	Test Accuracy	Test RMSE	Test Accuracy	Test RMSE
Single Layer	90.7	1.34	90.2	1.36
Single Layer with Dropout	89.9	1.45	90.2	1.42
Double Layer	90.1	1.40	90.9	1.30
Double Layer with Dropout	89.2	1.53	89.8	1.82
Logistic Regression	88.1	1.74	90.4	1.33
SVM (linear kernel)	89.4	1.52	90.7	1.37
SVM (polynomial kernel)	90.1	1.44	89.9	1.45
SVM (RBF kernel)	90.1	1.45	90.5	1.39