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Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		A1C: REAL_VALUED (STATIC_INPUT)
		FBG: REAL_VALUED (STATIC_INPUT)
		ogtt.2hr: REAL_VALUED (STATIC_INPUT)
		insulin: REAL_VALUED (STATIC_INPUT)
		hs.CRP: REAL_VALUED (STATIC_INPUT)
		Tchol: REAL_VALUED (STATIC_INPUT)
		Trg: REAL_VALUED (STATIC_INPUT)
		HDL: REAL_VALUED (STATIC_INPUT)
		LDL: REAL_VALUED (STATIC_INPUT)
		mean_glucose: REAL_VALUED (STATIC_INPUT)
		sd_glucose: REAL_VALUED (STATIC_INPUT)
		range_glucose: REAL_VALUED (STATIC_INPUT)
		min_glucose: REAL_VALUED (STATIC_INPUT)
		max_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.25_glucose: REAL_VALUED (STATIC_INPUT)
		median_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.75_glucose: REAL_VALUED (STATIC_INPUT)
		mean_slope: REAL_VALUED (STATIC_INPUT)
		max_slope: REAL_VALUED (STATIC_INPUT)
		number_Random140: REAL_VALUED (STATIC_INPUT)
		number_Random200: REAL_VALUED (STATIC_INPUT)
		percent_below.80: REAL_VALUED (STATIC_INPUT)
		se_glucose_mean: REAL_VALUED (STATIC_INPUT)
		numGE: REAL_VALUED (STATIC_INPUT)
		mage: REAL_VALUED (STATIC_INPUT)
		j_index: REAL_VALUED (STATIC_INPUT)
		IQR: REAL_VALUED (STATIC_INPUT)
		modd: REAL_VALUED (STATIC_INPUT)
		distance_traveled: REAL_VALUED (STATIC_INPUT)
		coef_variation: REAL_VALUED (STATIC_INPUT)
		number_Random140_normByDays: REAL_VALUED (STATIC_INPUT)
		number_Random200_normByDays: REAL_VALUED (STATIC_INPUT)
		numGE_normByDays: REAL_VALUED (STATIC_INPUT)
		distance_traveled_normByDays: REAL_VALUED (STATIC_INPUT)
		diagnosis: REAL_VALUED (STATIC_INPUT)
		freq_low: REAL_VALUED (STATIC_INPUT)
		freq_moderate: REAL_VALUED (STATIC_INPUT)
		freq_severe: REAL_VALUED (STATIC_INPUT)
		glucotype: REAL_VALUED (STATIC_INPUT)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Insulin_rate_dd: REAL_VALUED (STATIC_INPUT)
		perc_cgm_prediabetic_range: REAL_VALUED (STATIC_INPUT)
		perc_cgm_diabetic_range: REAL_VALUED (STATIC_INPUT)
		SSPG: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 160
	Extracted segments: 152
	Interpolated values: 8003
	Percent of values interpolated: 8.57%
Splitting data...
	Train: 57159 (68.64%)
	Val: 16704 (20.06%)
	Test: 19521 (23.44%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.060749299824237823, Current params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.060000000000000005, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 9.0, 'alpha': 0.056, 'lambda_': 0.269, 'n_estimators': 416}
Best value: 0.060749299824237823, Best params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.060000000000000005, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 9.0, 'alpha': 0.056, 'lambda_': 0.269, 'n_estimators': 416}
Current value: 0.049804091453552246, Current params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.482, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 6.0, 'alpha': 0.08700000000000001, 'lambda_': 0.1, 'n_estimators': 288}
Best value: 0.049804091453552246, Best params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.482, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 6.0, 'alpha': 0.08700000000000001, 'lambda_': 0.1, 'n_estimators': 288}
Current value: 0.050735924392938614, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.706, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.054, 'lambda_': 0.194, 'n_estimators': 320}
Best value: 0.049804091453552246, Best params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.482, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 6.0, 'alpha': 0.08700000000000001, 'lambda_': 0.1, 'n_estimators': 288}
Current value: 0.052117519080638885, Current params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.894, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 5.5, 'alpha': 0.23, 'lambda_': 0.13, 'n_estimators': 288}
Best value: 0.049804091453552246, Best params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.482, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 6.0, 'alpha': 0.08700000000000001, 'lambda_': 0.1, 'n_estimators': 288}
Current value: 0.04491623863577843, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.319, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.23900000000000002, 'lambda_': 0.069, 'n_estimators': 384}
Best value: 0.04491623863577843, Best params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.319, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.23900000000000002, 'lambda_': 0.069, 'n_estimators': 384}
Current value: 0.049396026879549026, Current params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.495, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 1.0, 'max_depth': 10, 'gamma': 8.5, 'alpha': 0.28900000000000003, 'lambda_': 0.23500000000000001, 'n_estimators': 480}
Best value: 0.04491623863577843, Best params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.319, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.23900000000000002, 'lambda_': 0.069, 'n_estimators': 384}
Current value: 0.04635065048933029, Current params: {'in_len': 48, 'max_samples_per_ts': 150, 'lr': 0.668, 'subsample': 0.7, 'min_child_weight': 1.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 2.5, 'alpha': 0.272, 'lambda_': 0.147, 'n_estimators': 288}
Best value: 0.04491623863577843, Best params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.319, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.23900000000000002, 'lambda_': 0.069, 'n_estimators': 384}
Current value: 0.04715649411082268, Current params: {'in_len': 72, 'max_samples_per_ts': 150, 'lr': 0.887, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 10, 'gamma': 2.0, 'alpha': 0.217, 'lambda_': 0.183, 'n_estimators': 384}
Best value: 0.04491623863577843, Best params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.319, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.23900000000000002, 'lambda_': 0.069, 'n_estimators': 384}
Current value: 0.044235896319150925, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.457, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.296, 'lambda_': 0.056, 'n_estimators': 448}
Best value: 0.044235896319150925, Best params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.457, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.296, 'lambda_': 0.056, 'n_estimators': 448}
Current value: 0.04693249613046646, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'lr': 0.34800000000000003, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 8.5, 'alpha': 0.298, 'lambda_': 0.294, 'n_estimators': 448}
Best value: 0.044235896319150925, Best params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.457, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.296, 'lambda_': 0.056, 'n_estimators': 448}
Current value: 0.04968827962875366, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'lr': 0.064, 'subsample': 0.6, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 3.5, 'alpha': 0.156, 'lambda_': 0.004, 'n_estimators': 512}
Best value: 0.044235896319150925, Best params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.457, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.296, 'lambda_': 0.056, 'n_estimators': 448}
Current value: 0.04462192952632904, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.254, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 1.0, 'alpha': 0.193, 'lambda_': 0.055, 'n_estimators': 384}
Best value: 0.044235896319150925, Best params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.457, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.296, 'lambda_': 0.056, 'n_estimators': 448}
Current value: 0.043827127665281296, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.281, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.164, 'lambda_': 0.029, 'n_estimators': 352}
Best value: 0.043827127665281296, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.281, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.164, 'lambda_': 0.029, 'n_estimators': 352}
Current value: 0.04675828292965889, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.219, 'subsample': 0.6, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 4.0, 'alpha': 0.121, 'lambda_': 0.006, 'n_estimators': 352}
Best value: 0.043827127665281296, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.281, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.164, 'lambda_': 0.029, 'n_estimators': 352}
Current value: 0.04358788952231407, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.044155560433864594, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'lr': 0.682, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.014000000000000002, 'lambda_': 0.032, 'n_estimators': 448}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04680765047669411, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.594, 'subsample': 0.6, 'min_child_weight': 2.0, 'colsample_bytree': 0.8, 'max_depth': 6, 'gamma': 4.0, 'alpha': 0.152, 'lambda_': 0.1, 'n_estimators': 352}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.0478767529129982, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.795, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 7.0, 'alpha': 0.114, 'lambda_': 0.08800000000000001, 'n_estimators': 512}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04781796410679817, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'lr': 0.98, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 5, 'gamma': 2.5, 'alpha': 0.184, 'lambda_': 0.04, 'n_estimators': 256}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.045567478984594345, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'lr': 0.135, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 2.0, 'alpha': 0.001, 'lambda_': 0.113, 'n_estimators': 416}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04686334356665611, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'lr': 0.394, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 3.5, 'alpha': 0.044000000000000004, 'lambda_': 0.17300000000000001, 'n_estimators': 352}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.043681178241968155, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'lr': 0.5700000000000001, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.007, 'lambda_': 0.032, 'n_estimators': 448}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04381394013762474, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'lr': 0.5660000000000001, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.02, 'lambda_': 0.025, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04397082328796387, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'lr': 0.612, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.034, 'lambda_': 0.07100000000000001, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.045368168503046036, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'lr': 0.759, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 2.0, 'alpha': 0.027000000000000003, 'lambda_': 0.001, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04486231878399849, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'lr': 0.5670000000000001, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.08, 'lambda_': 0.028, 'n_estimators': 416}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.0444110669195652, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'lr': 0.555, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 3.0, 'alpha': 0.077, 'lambda_': 0.083, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04628457874059677, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'lr': 0.421, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 4.5, 'alpha': 0.011, 'lambda_': 0.048, 'n_estimators': 512}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04422561079263687, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'lr': 0.798, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 0.5, 'alpha': 0.115, 'lambda_': 0.016, 'n_estimators': 448}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.049196042120456696, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'lr': 0.642, 'subsample': 0.8, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 7, 'gamma': 7.0, 'alpha': 0.056, 'lambda_': 0.219, 'n_estimators': 416}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04579123109579086, Current params: {'in_len': 72, 'max_samples_per_ts': 200, 'lr': 0.739, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.068, 'lambda_': 0.134, 'n_estimators': 416}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.044117383658885956, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.557, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.023, 'lambda_': 0.025, 'n_estimators': 448}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.0460420697927475, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.28300000000000003, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.179, 'lambda_': 0.064, 'n_estimators': 320}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04373803734779358, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'lr': 0.5, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 1.5, 'alpha': 0.1, 'lambda_': 0.042, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04614515230059624, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'lr': 0.51, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 2.5, 'alpha': 0.092, 'lambda_': 0.044000000000000004, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04558504745364189, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'lr': 0.511, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 1.5, 'alpha': 0.002, 'lambda_': 0.108, 'n_estimators': 512}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04444320499897003, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'lr': 0.433, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.041, 'lambda_': 0.083, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.045447882264852524, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.365, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 8, 'gamma': 5.5, 'alpha': 0.1, 'lambda_': 0.018000000000000002, 'n_estimators': 448}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.046181339770555496, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'lr': 0.722, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 3.0, 'alpha': 0.056, 'lambda_': 0.068, 'n_estimators': 480}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.048888470977544785, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.491, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 10.0, 'alpha': 0.139, 'lambda_': 0.127, 'n_estimators': 384}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.04439609497785568, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'lr': 0.635, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 2.0, 'alpha': 0.018000000000000002, 'lambda_': 0.043000000000000003, 'n_estimators': 416}
Best value: 0.04358788952231407, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.642, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.004, 'lambda_': 0.05, 'n_estimators': 448}
Current value: 0.042959894984960556, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.04468943178653717, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'lr': 0.095, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.137, 'lambda_': 0.014000000000000002, 'n_estimators': 256}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.044100746512413025, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'lr': 0.165, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.251, 'lambda_': 0.035, 'n_estimators': 320}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.045537177473306656, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.686, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.20400000000000001, 'lambda_': 0.055, 'n_estimators': 448}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.04474601149559021, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.8240000000000001, 'subsample': 0.6, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.046, 'lambda_': 0.016, 'n_estimators': 288}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.049183882772922516, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'lr': 0.02, 'subsample': 0.7, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.031, 'lambda_': 0.254, 'n_estimators': 480}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.04688921198248863, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.889, 'subsample': 0.8, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 2.0, 'alpha': 0.062, 'lambda_': 0.07300000000000001, 'n_estimators': 512}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.04632322117686272, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.586, 'subsample': 0.6, 'min_child_weight': 2.0, 'colsample_bytree': 0.8, 'max_depth': 4, 'gamma': 2.5, 'alpha': 0.012, 'lambda_': 0.051000000000000004, 'n_estimators': 448}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
Current value: 0.04519790783524513, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'lr': 0.53, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.166, 'n_estimators': 512}
Best value: 0.042959894984960556, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.17200000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.167, 'lambda_': 0.017, 'n_estimators': 320}
--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		A1C: REAL_VALUED (STATIC_INPUT)
		FBG: REAL_VALUED (STATIC_INPUT)
		ogtt.2hr: REAL_VALUED (STATIC_INPUT)
		insulin: REAL_VALUED (STATIC_INPUT)
		hs.CRP: REAL_VALUED (STATIC_INPUT)
		Tchol: REAL_VALUED (STATIC_INPUT)
		Trg: REAL_VALUED (STATIC_INPUT)
		HDL: REAL_VALUED (STATIC_INPUT)
		LDL: REAL_VALUED (STATIC_INPUT)
		mean_glucose: REAL_VALUED (STATIC_INPUT)
		sd_glucose: REAL_VALUED (STATIC_INPUT)
		range_glucose: REAL_VALUED (STATIC_INPUT)
		min_glucose: REAL_VALUED (STATIC_INPUT)
		max_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.25_glucose: REAL_VALUED (STATIC_INPUT)
		median_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.75_glucose: REAL_VALUED (STATIC_INPUT)
		mean_slope: REAL_VALUED (STATIC_INPUT)
		max_slope: REAL_VALUED (STATIC_INPUT)
		number_Random140: REAL_VALUED (STATIC_INPUT)
		number_Random200: REAL_VALUED (STATIC_INPUT)
		percent_below.80: REAL_VALUED (STATIC_INPUT)
		se_glucose_mean: REAL_VALUED (STATIC_INPUT)
		numGE: REAL_VALUED (STATIC_INPUT)
		mage: REAL_VALUED (STATIC_INPUT)
		j_index: REAL_VALUED (STATIC_INPUT)
		IQR: REAL_VALUED (STATIC_INPUT)
		modd: REAL_VALUED (STATIC_INPUT)
		distance_traveled: REAL_VALUED (STATIC_INPUT)
		coef_variation: REAL_VALUED (STATIC_INPUT)
		number_Random140_normByDays: REAL_VALUED (STATIC_INPUT)
		number_Random200_normByDays: REAL_VALUED (STATIC_INPUT)
		numGE_normByDays: REAL_VALUED (STATIC_INPUT)
		distance_traveled_normByDays: REAL_VALUED (STATIC_INPUT)
		diagnosis: REAL_VALUED (STATIC_INPUT)
		freq_low: REAL_VALUED (STATIC_INPUT)
		freq_moderate: REAL_VALUED (STATIC_INPUT)
		freq_severe: REAL_VALUED (STATIC_INPUT)
		glucotype: REAL_VALUED (STATIC_INPUT)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Insulin_rate_dd: REAL_VALUED (STATIC_INPUT)
		perc_cgm_prediabetic_range: REAL_VALUED (STATIC_INPUT)
		perc_cgm_diabetic_range: REAL_VALUED (STATIC_INPUT)
		SSPG: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 160
	Extracted segments: 152
	Interpolated values: 8003
	Percent of values interpolated: 8.57%
Splitting data...
	Train: 62461 (61.57%)
	Val: 12357 (12.18%)
	Test: 16517 (16.28%)
	Test OOD: 10113 (9.97%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [254.19214    9.832601]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [184.9846     9.117277]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [61.09881   6.821616]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [65.34495    7.1352844]
		Model Seed: 10 Seed: 1 ID likelihoods: -9.68798365942052
		Model Seed: 10 Seed: 1 OOD likelihoods: -9.529074874125481
		Model Seed: 10 Seed: 1 ID calibration errors: [0.36849534 0.21424599 0.13879951 0.09500194 0.06956265 0.04998913
 0.03550295 0.02664255 0.01944604 0.01528257 0.01291256 0.01089645]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.29000675 0.16133407 0.11439779 0.08600486 0.07138366 0.06248984
 0.0535996  0.04637411 0.05018307 0.04894276 0.04456916 0.04055984]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [268.8239     9.933746]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [188.68208    9.045698]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [62.91681    6.9362106]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [53.88266    6.3185015]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.715966250032423
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.538969959172771
		Model Seed: 10 Seed: 2 ID calibration errors: [0.36791016 0.22645455 0.14929445 0.10318091 0.07356039 0.0529301
 0.03813604 0.03073474 0.02263174 0.01838678 0.01619404 0.01431745]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.33896542 0.18490221 0.11558248 0.0767843  0.04959467 0.03283588
 0.02256519 0.01690901 0.01323696 0.00957908 0.00746882 0.00464994]
	Model Seed: 10 ID mean of (MSE, MAE): [261.50803    9.883173]
	Model Seed: 10 OOD mean of (MSE, MAE): [186.83334    9.081488]
	Model Seed: 10 ID median of (MSE, MAE): [62.00781    6.8789134]
	Model Seed: 10 OOD median of (MSE, MAE): [59.613804  6.726893]
	Model Seed: 10 ID likelihoods: -9.701974954726472
	Model Seed: 10 OOD likelihoods: -9.534022416649126
	Model Seed: 10 ID calibration errors: [0.36820275 0.22035027 0.14404698 0.09909142 0.07156152 0.05145961
 0.03681949 0.02868865 0.02103889 0.01683467 0.0145533  0.01260695]
	Model Seed: 10 OOD calibration errors: [0.31448608 0.17311814 0.11499014 0.08139458 0.06048917 0.04766286
 0.0380824  0.03164156 0.03171001 0.02926092 0.02601899 0.02260489]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [251.51399    9.692509]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [187.55992    9.378094]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [60.80361    6.6822553]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [70.419106   7.3556747]
		Model Seed: 11 Seed: 1 ID likelihoods: -9.682688269587736
		Model Seed: 11 Seed: 1 OOD likelihoods: -9.535988167869501
		Model Seed: 11 Seed: 1 ID calibration errors: [0.38956927 0.23333174 0.14601727 0.09769094 0.07278879 0.05034024
 0.03655818 0.02947419 0.02135352 0.01806194 0.01658238 0.01266588]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.32935268 0.1837291  0.13073018 0.10086399 0.08803288 0.0788834
 0.07491695 0.0733591  0.07429644 0.07858629 0.07092721 0.06713911]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [269.46536    9.963679]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [180.4838     8.824383]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [66.93398    7.1477914]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [55.27841    6.3287306]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.717158631695039
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.51675890452348
		Model Seed: 11 Seed: 2 ID calibration errors: [0.3983667  0.24093688 0.15039361 0.09917521 0.06986863 0.05070707
 0.03357776 0.02655972 0.01911657 0.01671033 0.01517702 0.01196475]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.3517928  0.19305981 0.11607143 0.07583333 0.04703515 0.02755952
 0.02005102 0.01530329 0.01141015 0.00906463 0.0073852  0.00540108]
	Model Seed: 11 ID mean of (MSE, MAE): [260.4897      9.8280945]
	Model Seed: 11 OOD mean of (MSE, MAE): [184.02185    9.101238]
	Model Seed: 11 ID median of (MSE, MAE): [63.868797   6.9150233]
	Model Seed: 11 OOD median of (MSE, MAE): [62.84876    6.8422027]
	Model Seed: 11 ID likelihoods: -9.699923450641387
	Model Seed: 11 OOD likelihoods: -9.526373536196491
	Model Seed: 11 ID calibration errors: [0.39396798 0.23713431 0.14820544 0.09843307 0.07132871 0.05052366
 0.03506797 0.02801695 0.02023504 0.01738614 0.0158797  0.01231531]
	Model Seed: 11 OOD calibration errors: [0.34057274 0.18839445 0.1234008  0.08834866 0.06753401 0.05322146
 0.04748399 0.04433119 0.04285329 0.04382546 0.03915621 0.0362701 ]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [255.43927    9.695401]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [180.68826    9.017508]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [58.61187    6.6090264]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [64.36712    7.0462613]
		Model Seed: 12 Seed: 1 ID likelihoods: -9.690431177214485
		Model Seed: 12 Seed: 1 OOD likelihoods: -9.517325492093573
		Model Seed: 12 Seed: 1 ID calibration errors: [0.38353223 0.22293372 0.14233897 0.09649556 0.07440321 0.05465244
 0.04027    0.03236289 0.02384223 0.01991356 0.01829465 0.01693269]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.30557614 0.16460526 0.11172424 0.08284813 0.06561656 0.05629158
 0.05239216 0.04497116 0.04481711 0.04293199 0.03954947 0.03361974]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [271.31378    9.999465]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [178.06888    8.820427]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [63.05174    6.8978252]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [53.69926   6.411806]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.720576260633987
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.510023877478545
		Model Seed: 12 Seed: 2 ID calibration errors: [0.40593111 0.24403768 0.15042947 0.10130558 0.0732008  0.05168654
 0.03683579 0.02702942 0.0218968  0.0180456  0.01620287 0.01398637]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.36300595 0.19277069 0.1117602  0.07078656 0.0438407  0.02800595
 0.0209212  0.01786565 0.01163265 0.01088152 0.00857285 0.0058631 ]
	Model Seed: 12 ID mean of (MSE, MAE): [263.37653    9.847433]
	Model Seed: 12 OOD mean of (MSE, MAE): [179.37857    8.918967]
	Model Seed: 12 ID median of (MSE, MAE): [60.831802   6.7534256]
	Model Seed: 12 OOD median of (MSE, MAE): [59.033188   6.7290335]
	Model Seed: 12 ID likelihoods: -9.705503718924236
	Model Seed: 12 OOD likelihoods: -9.513674684786059
	Model Seed: 12 ID calibration errors: [0.39473167 0.2334857  0.14638422 0.09890057 0.07380201 0.05316949
 0.03855289 0.02969615 0.02286951 0.01897958 0.01724876 0.01545953]
	Model Seed: 12 OOD calibration errors: [0.33429105 0.17868798 0.11174222 0.07681735 0.05472863 0.04214877
 0.03665668 0.03141841 0.02822488 0.02690676 0.02406116 0.01974142]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [253.28107    9.785551]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [200.52893   10.052569]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [65.137054  7.068046]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [93.32937   8.519814]
		Model Seed: 13 Seed: 1 ID likelihoods: -9.686187895222163
		Model Seed: 13 Seed: 1 OOD likelihoods: -9.569417911806864
		Model Seed: 13 Seed: 1 ID calibration errors: [0.40272342 0.23132441 0.13919372 0.0915732  0.06294418 0.04428904
 0.03019676 0.02263628 0.01673061 0.01385537 0.01231447 0.01022016]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.34123602 0.19593184 0.14539811 0.12175919 0.12207988 0.12812995
 0.13502332 0.13948795 0.14681334 0.14572194 0.14421825 0.13570242]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [263.05188    9.931544]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [175.88426    8.744243]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [67.53994  7.20771]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [55.4549  6.3398]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.705114344542956
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.50385175180336
		Model Seed: 13 Seed: 2 ID calibration errors: [0.40265026 0.23760975 0.14693733 0.09694251 0.06321595 0.04511979
 0.03000937 0.02169371 0.0158639  0.01359797 0.0106807  0.00813185]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.36649518 0.19649235 0.11635629 0.0759042  0.04583192 0.02734269
 0.018322   0.01453656 0.009178   0.00754252 0.00660147 0.0044076 ]
	Model Seed: 13 ID mean of (MSE, MAE): [258.16647    9.858547]
	Model Seed: 13 OOD mean of (MSE, MAE): [188.2066     9.398406]
	Model Seed: 13 ID median of (MSE, MAE): [66.3385    7.137878]
	Model Seed: 13 OOD median of (MSE, MAE): [74.392136   7.4298067]
	Model Seed: 13 ID likelihoods: -9.695651119882559
	Model Seed: 13 OOD likelihoods: -9.536634831805113
	Model Seed: 13 ID calibration errors: [0.40268684 0.23446708 0.14306552 0.09425786 0.06308007 0.04470442
 0.03010307 0.02216499 0.01629725 0.01372667 0.01149758 0.009176  ]
	Model Seed: 13 OOD calibration errors: [0.3538656  0.19621209 0.1308772  0.09883169 0.0839559  0.07773632
 0.07667266 0.07701226 0.07799567 0.07663223 0.07540986 0.07005501]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [260.1119     9.802816]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [194.11066     9.8096895]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [63.306175   6.9753094]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [82.99722    7.9821606]
		Model Seed: 14 Seed: 1 ID likelihoods: -9.699494744674386
		Model Seed: 14 Seed: 1 OOD likelihoods: -9.553152650599836
		Model Seed: 14 Seed: 1 ID calibration errors: [0.39736486 0.23392344 0.14454778 0.09761244 0.06986578 0.05300949
 0.0362354  0.02836599 0.01947606 0.01836228 0.01553772 0.0137655 ]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.33180729 0.18126391 0.12288889 0.09268487 0.08324942 0.08297003
 0.08307407 0.08560585 0.09174309 0.09369766 0.0815115  0.08205784]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [274.08987   10.105398]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [177.0431     8.805535]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [67.07964    7.1134834]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [56.16175    6.5743656]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.725666674986636
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.50713528253171
		Model Seed: 14 Seed: 2 ID calibration errors: [0.41000339 0.24539356 0.15271823 0.09809015 0.06877021 0.04872931
 0.0330092  0.02558077 0.02085097 0.01784451 0.01612484 0.01341928]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.37483418 0.19635913 0.11205215 0.07157171 0.04363237 0.02711876
 0.02072562 0.01560799 0.01109552 0.00973356 0.00749433 0.00536139]
	Model Seed: 14 ID mean of (MSE, MAE): [267.1009     9.954107]
	Model Seed: 14 OOD mean of (MSE, MAE): [185.57687    9.307612]
	Model Seed: 14 ID median of (MSE, MAE): [65.19291    7.0443964]
	Model Seed: 14 OOD median of (MSE, MAE): [69.57948   7.278263]
	Model Seed: 14 ID likelihoods: -9.712580709830512
	Model Seed: 14 OOD likelihoods: -9.530143966565774
	Model Seed: 14 ID calibration errors: [0.40368412 0.2396585  0.14863301 0.09785129 0.06931799 0.0508694
 0.0346223  0.02697338 0.02016351 0.01810339 0.01583128 0.01359239]
	Model Seed: 14 OOD calibration errors: [0.35332074 0.18881152 0.11747052 0.08212829 0.0634409  0.0550444
 0.05189985 0.05060692 0.05141931 0.05171561 0.04450292 0.04370962]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [256.44525     9.8871155]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [199.41771   9.96927]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [65.473274   7.0927153]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [84.87153  8.16263]
		Model Seed: 15 Seed: 1 ID likelihoods: -9.692396191329216
		Model Seed: 15 Seed: 1 OOD likelihoods: -9.56663974917642
		Model Seed: 15 Seed: 1 ID calibration errors: [0.3776888  0.22411155 0.13629096 0.09442988 0.06497265 0.04753503
 0.03162376 0.02519481 0.01832338 0.01523349 0.0146771  0.01471081]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.32029509 0.18227957 0.11695944 0.08950885 0.0798346  0.07622943
 0.07670932 0.07546572 0.08320069 0.08605302 0.08362642 0.08005125]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [272.25287    9.983809]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [180.18767    8.837611]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [67.54347   7.159165]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [54.058777  6.379755]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.722304350638268
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.515938071342134
		Model Seed: 15 Seed: 2 ID calibration errors: [0.40745222 0.24593109 0.15125108 0.10519181 0.06994046 0.05171263
 0.0349124  0.02670433 0.01997393 0.01800069 0.01642931 0.01389718]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.37172761 0.19668226 0.11615221 0.07379393 0.04538407 0.02860828
 0.02278203 0.01569019 0.00919643 0.00920351 0.00695153 0.00524943]
	Model Seed: 15 ID mean of (MSE, MAE): [264.34906    9.935463]
	Model Seed: 15 OOD mean of (MSE, MAE): [189.80269   9.40344]
	Model Seed: 15 ID median of (MSE, MAE): [66.50838    7.1259403]
	Model Seed: 15 OOD median of (MSE, MAE): [69.46515    7.2711926]
	Model Seed: 15 ID likelihoods: -9.707350270983742
	Model Seed: 15 OOD likelihoods: -9.541288910259278
	Model Seed: 15 ID calibration errors: [0.39257051 0.23502132 0.14377102 0.09981084 0.06745656 0.04962383
 0.03326808 0.02594957 0.01914866 0.01661709 0.0155532  0.014304  ]
	Model Seed: 15 OOD calibration errors: [0.34601135 0.18948091 0.11655583 0.08165139 0.06260934 0.05241885
 0.04974567 0.04557796 0.04619856 0.04762827 0.04528897 0.04265034]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [258.91418    9.820263]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [195.93867    9.751565]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [62.91913    6.8230324]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [81.03866   7.887053]
		Model Seed: 16 Seed: 1 ID likelihoods: -9.697187164418956
		Model Seed: 16 Seed: 1 OOD likelihoods: -9.557839280014495
		Model Seed: 16 Seed: 1 ID calibration errors: [0.39883345 0.22829387 0.14418789 0.09642623 0.06771412 0.04569568
 0.03057341 0.02478684 0.01889872 0.01422983 0.01363792 0.01038006]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.3310663  0.18020352 0.12574993 0.10077711 0.09461028 0.09352717
 0.0959139  0.09553791 0.0984867  0.09834679 0.09377841 0.0885778 ]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [270.47488   10.088173]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [179.59068    8.896729]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [69.13913    7.3350887]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [59.108734   6.6854963]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.719027816626289
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.514278714705824
		Model Seed: 16 Seed: 2 ID calibration errors: [0.40001359 0.23400771 0.14555999 0.09755934 0.06550408 0.04718012
 0.03225301 0.02452369 0.01802719 0.01702827 0.01404221 0.01183549]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.36521117 0.18978883 0.11048044 0.07044359 0.04515164 0.02708333
 0.02056406 0.01532029 0.01017999 0.00784864 0.00680981 0.00589144]
	Model Seed: 16 ID mean of (MSE, MAE): [264.69452    9.954218]
	Model Seed: 16 OOD mean of (MSE, MAE): [187.76468    9.324147]
	Model Seed: 16 ID median of (MSE, MAE): [66.02913    7.0790606]
	Model Seed: 16 OOD median of (MSE, MAE): [70.0737    7.286275]
	Model Seed: 16 ID likelihoods: -9.708107490522622
	Model Seed: 16 OOD likelihoods: -9.53605899736016
	Model Seed: 16 ID calibration errors: [0.39942352 0.23115079 0.14487394 0.09699279 0.0666091  0.0464379
 0.03141321 0.02465526 0.01846296 0.01562905 0.01384007 0.01110777]
	Model Seed: 16 OOD calibration errors: [0.34813874 0.18499618 0.11811519 0.08561035 0.06988096 0.06030525
 0.05823898 0.0554291  0.05433334 0.05309771 0.05029411 0.04723462]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [256.5915    9.93594]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [195.9123     9.761427]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [64.80747    7.1294413]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [79.628456  7.771627]
		Model Seed: 17 Seed: 1 ID likelihoods: -9.69268123956969
		Model Seed: 17 Seed: 1 OOD likelihoods: -9.557772069071488
		Model Seed: 17 Seed: 1 ID calibration errors: [0.37043993 0.20796078 0.13238902 0.08867393 0.06531967 0.04763657
 0.02922432 0.02354807 0.01751901 0.01340192 0.01159808 0.0102472 ]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.30280027 0.17051556 0.12101949 0.10478257 0.09263842 0.09055194
 0.09457313 0.0975565  0.10899625 0.11800754 0.11264115 0.11554607]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [274.73242    9.973123]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [180.05164    8.790798]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [63.13684    6.8917747]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [53.21167    6.2625523]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.726837006271321
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.515560540191434
		Model Seed: 17 Seed: 2 ID calibration errors: [0.40477117 0.23958994 0.15202599 0.10314641 0.07566773 0.05474064
 0.03796639 0.02876066 0.02352445 0.01970574 0.01801079 0.01433533]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.3708716  0.19656037 0.11550028 0.08005385 0.04930414 0.03292375
 0.02407455 0.01724348 0.01259212 0.01134495 0.00882795 0.008339  ]
	Model Seed: 17 ID mean of (MSE, MAE): [265.66196    9.954531]
	Model Seed: 17 OOD mean of (MSE, MAE): [187.98196    9.276113]
	Model Seed: 17 ID median of (MSE, MAE): [63.972157   7.0106077]
	Model Seed: 17 OOD median of (MSE, MAE): [66.42006  7.01709]
	Model Seed: 17 ID likelihoods: -9.709759122920506
	Model Seed: 17 OOD likelihoods: -9.53666630463146
	Model Seed: 17 ID calibration errors: [0.38760555 0.22377536 0.1422075  0.09591017 0.0704937  0.05118861
 0.03359536 0.02615437 0.02052173 0.01655383 0.01480443 0.01229126]
	Model Seed: 17 OOD calibration errors: [0.33683594 0.18353797 0.11825989 0.09241821 0.07097128 0.06173785
 0.05932384 0.05739999 0.06079418 0.06467625 0.06073455 0.06194253]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [257.8389     9.843843]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [200.23509   10.093862]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [68.97424   7.173976]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [93.33456   8.615369]
		Model Seed: 18 Seed: 1 ID likelihoods: -9.69510571849979
		Model Seed: 18 Seed: 1 OOD likelihoods: -9.568684296912252
		Model Seed: 18 Seed: 1 ID calibration errors: [0.40325377 0.23277315 0.14240939 0.09568561 0.06635116 0.04752925
 0.03250004 0.02423503 0.01816897 0.01460079 0.01299285 0.01051512]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.34418681 0.18820187 0.13736775 0.11223472 0.10929436 0.11752936
 0.12563375 0.13226217 0.14359916 0.15455745 0.15672595 0.15300517]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [267.201     10.017703]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [181.83322    8.846331]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [65.22071    7.1157584]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [53.428406   6.2644954]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.71293887585069
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.520483777521122
		Model Seed: 18 Seed: 2 ID calibration errors: [0.40588063 0.23821166 0.15073405 0.09969287 0.0667591  0.04808523
 0.03191257 0.02395292 0.01639071 0.01538295 0.01295326 0.01212755]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.36488095 0.19572562 0.11537557 0.07598498 0.04970522 0.031875
 0.02267432 0.01592971 0.01186933 0.01009495 0.0089966  0.00673895]
	Model Seed: 18 ID mean of (MSE, MAE): [262.51996    9.930773]
	Model Seed: 18 OOD mean of (MSE, MAE): [191.03415    9.470097]
	Model Seed: 18 ID median of (MSE, MAE): [67.09747   7.144867]
	Model Seed: 18 OOD median of (MSE, MAE): [73.381485  7.439932]
	Model Seed: 18 ID likelihoods: -9.70402229717524
	Model Seed: 18 OOD likelihoods: -9.544584037216687
	Model Seed: 18 ID calibration errors: [0.4045672  0.2354924  0.14657172 0.09768924 0.06655513 0.04780724
 0.0322063  0.02409398 0.01727984 0.01499187 0.01297306 0.01132133]
	Model Seed: 18 OOD calibration errors: [0.35453388 0.19196375 0.12637166 0.09410985 0.07949979 0.07470218
 0.07415403 0.07409594 0.07773425 0.0823262  0.08286128 0.07987206]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [256.96695    9.790853]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [194.87036     9.7235565]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [63.204937  6.85246 ]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [79.626976  7.733473]
		Model Seed: 19 Seed: 1 ID likelihoods: -9.693412745904125
		Model Seed: 19 Seed: 1 OOD likelihoods: -9.555105990847878
		Model Seed: 19 Seed: 1 ID calibration errors: [0.3934745  0.23112691 0.14781093 0.09950296 0.07327646 0.04977327
 0.03327588 0.02668384 0.01896994 0.01569333 0.01361827 0.01063601]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.32425896 0.18764967 0.13042035 0.10608433 0.09564995 0.09277747
 0.09671748 0.09646553 0.10353397 0.10907399 0.10051515 0.09691998]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [267.58585    9.988911]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [176.85623    8.755235]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [69.513664   7.3157005]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [55.180466  6.385251]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.71365926356026
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.50660715243249
		Model Seed: 19 Seed: 2 ID calibration errors: [0.40550201 0.24117205 0.14631944 0.09817797 0.06562724 0.047379
 0.02999486 0.02177669 0.01485488 0.01220633 0.01054008 0.0098126 ]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.37101899 0.19738662 0.11196003 0.07268282 0.04607426 0.02862245
 0.02071003 0.0163818  0.01079365 0.00935941 0.00749433 0.00544501]
	Model Seed: 19 ID mean of (MSE, MAE): [262.2764     9.889881]
	Model Seed: 19 OOD mean of (MSE, MAE): [185.8633     9.239395]
	Model Seed: 19 ID median of (MSE, MAE): [66.3593   7.08408]
	Model Seed: 19 OOD median of (MSE, MAE): [67.40372   7.059362]
	Model Seed: 19 ID likelihoods: -9.703536004732193
	Model Seed: 19 OOD likelihoods: -9.530856571640184
	Model Seed: 19 ID calibration errors: [0.39948825 0.23614948 0.14706519 0.09884046 0.06945185 0.04857614
 0.03163537 0.02423027 0.01691241 0.01394983 0.01207918 0.01022431]
	Model Seed: 19 OOD calibration errors: [0.34763898 0.19251815 0.12119019 0.08938358 0.07086211 0.06069996
 0.05871376 0.05642367 0.05716381 0.0592167  0.05400474 0.0511825 ]
ID mean of (MSE, MAE): [263.01434326171875, 9.903620719909668] +- [2.477480173110962, 0.045773059129714966] +- [6.884833   0.09493293] 
OOD mean of (MSE, MAE): [186.64639282226562, 9.252090454101562] +- [3.1013660430908203, 0.16238461434841156] +- [6.778247  0.4153914] 
ID median of (MSE, MAE): [64.82062530517578, 7.017419338226318] +- [1.993780493736267, 0.12284501641988754] +- [1.3869677  0.09463149] 
OOD median of (MSE, MAE): [67.22114562988281, 7.108004570007324] +- [5.028065204620361, 0.259090393781662] +- [12.27464575  0.71292966] 
ID likelihoods: -9.704840914033948 +- 0.004698088223587382 +- 0.013084033449839438 
OOD likelihoods: -9.533030425711033 +- 0.008185794583359036 +- 0.01806962254074662 
ID calibration errors: [0.3946928412189993, 0.23266852043021596, 0.1454824542389038, 0.09777777246919703, 0.06896566308760983, 0.04943602916010008, 0.03372840418096114, 0.026062356907121952, 0.01929298127230548, 0.01627721147629686, 0.014426056302453314, 0.012239886472256798] +- [0.010220622268661085, 0.005757290810307119, 0.002092177891589005, 0.001586998507443783, 0.002944312596417014, 0.0024320204715772512, 0.0024668684498145533, 0.0022175189177340835, 0.0019595637541881834, 0.0016237131651892908, 0.0017327323655542055, 0.001793720610261803] +- [6.1552835e-03 6.6659655e-03 4.0839100e-03 2.4685035e-03 2.4579600e-04
 3.9101450e-04 1.3233450e-04 3.3069200e-04 2.0133000e-05 4.1370450e-04
 2.0945600e-04 1.4289850e-04] 
OOD calibration errors: [0.3429695077294482, 0.18677211277354322, 0.11989736396393806, 0.0870693945477599, 0.0683972076767345, 0.058567790581855995, 0.05509718509557572, 0.05239369912676854, 0.05284273097974407, 0.05352861013267855, 0.050233278130148426, 0.047526308173912006] +- [0.011607633069211714, 0.00654683031909654, 0.005384411367608691, 0.006455443752602339, 0.008297107336020876, 0.010548335532635275, 0.012632724354746884, 0.014535621483970834, 0.015921581289826667, 0.01717493641901985, 0.01809488096327355, 0.01825703157363649] +- [0.02091088 0.00720068 0.00576825 0.01268547 0.02184179 0.02937023
 0.03375818 0.0363149  0.04172425 0.04406333 0.04257299 0.04179161] 
