Table 7.

A summary of the top forecasting methods used with each house to forecast the sleep scores. Each house shows the machine learning algorithm that performed the best and the corresponding NMAE and NRMSE for each forecasting method. If the NMAE error was less than 2% we highlighted with blue, and if the NMAE error was between 2-4% we highlighted with yellow.

Side by Side Comparison of Results for Original Scores and Normalized Scores when Forecasting for Sleep Scores
	Original Scores									Normalized Scores
	Independent Prediction			Cross Prediction			Joint Prediction			Independent Prediction			Cross Prediction			Joint Prediction
	algorithm	NMAE	NRMSE	algorithm	NMAE	NRMSE	algorithm	NMAE	NRMSE	algorithm	NMAE	NRMSE	algorithm	NMAE	NRMSE	algorithm	NMAE	NRMSE
HH101	svm	0.049	0.084	svm	0.059	0.111	svm	0.059	0.111	logistic	0.002	0.004	logistic	0.002	0.004	logistic	0.002	0.004	HH101
HH102	svm	0.018	0.041	svm	0.106	0.151	svm	0.106	0.151	forest	0.002	0.003	forest	0.002	0.003	linear	0.002	0.003	HH102
HH103	svm	0.017	0.116	tree	0.041	0.089	tree	0.044	0.095	logistic	0.002	0.005	logistic	0.002	0.004	logistic	0.002	0.005	HH103
HH104	forest	0.047	0.083	forest	0.105	0.147	forest	0.104	0.142	svm	0.002	0.002	forest	0.002	0.002	forest	0.002	0.002	HH104
HH105	svm	0.024	0.116	svm	0.097	0.142	svm	0.097	0.142	logistic	0.002	0.003	logistic	0.002	0.003	logistic	0.002	0.003	HH105
HH106	svm	0.057	0.139	svm	0.132	0.179	svm	0.132	0.179	svm	0.004	0.005	forest	0.004	0.005	forest	0.004	0.005	HH106
HH108	svm	0.069	0.167	svm	0.098	0.149	svm	0.098	0.149	tree	0.002	0.004	logistic	0.002	0.004	tree	0.002	0.004	HH108
HH109	svm	0.060	0.112	svm	0.064	0.112	svm	0.064	0.112	forest	0.001	0.002	forest	0.001	0.002	forest	0.001	0.002	HH109
HH110	logistic	0.029	0.031	tree	0.104	0.106	tree	0.100	0.209	logistic	0.003	0.005	tree	0.003	0.003	tree	0.003	0.003	HH110
HH111	svm	0.025	0.042	forest	0.116	0.152	svm	0.117	0.154	forest	0.002	0.003	forest	0.002	0.003	forest	0.002	0.003	HH111
HH112	svm	0.045	0.075	svm	0.125	0.173	tree	0.121	0.169	forest	0.003	0.004	svm	0.003	0.004	svm	0.003	0.004	HH112
HH113	svm	0.030	0.097	logistic	0.091	0.156	logistic	0.091	0.156	logistic	0.002	0.004	logistic	0.002	0.004	logistic	0.002	0.004	HH113
HH114	forest	0.098	0.153	svm	0.091	0.139	svm	0.091	0.139	logistic	0.002	0.004	logistic	0.002	0.004	logistic	0.002	0.004	HH114
HH116	svm	0.023	0.080	svm	0.069	0.114	svm	0.069	0.114	logistic	0.002	0.003	logistic	0.002	0.003	logistic	0.002	0.003	HH116
HH117	forest	0.019	0.023	tree	0.000	0.000	tree	0.000	0.000	logistic	0.000	0.000	logistic	0.000	0.000	logistic	0.000	0.000	HH117
HH118	svm	0.044	0.055	tree	0.075	0.125	tree	0.057	0.082	forest	0.002	0.002	tree	0.002	0.002	tree	0.002	0.003	HH118
HH119	svm	0.046	0.069	svm	0.101	0.155	svm	0.101	0.155	logistic	0.002	0.004	logistic	0.002	0.004	logistic	0.002	0.004	HH119
HH120	svm	0.044	0.068	svm	0.075	0.097	svm	0.075	0.097	logistic	0.001	0.002	logistic	0.002	0.003	logistic	0.001	0.002	HH120
HH122	tree	0.020	0.026	tree	0.009	0.016	tree	0.006	0.012	logistic	0.001	0.001	tree	0.000	0.000	tree	0.000	0.000	HH122
HH123	svm	0.045	0.137	forest	0.136	0.183	forest	0.126	0.168	forest	0.004	0.005	logistic	0.004	0.005	forest	0.004	0.005	HH123