Table A1 Results of the feature...

Table A1

Results of the feature selection tests

	Model	Features	#Features	MeanAR2	MeanR2	MeanRMSE
FS1 (Belgium)	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Forward	M2	[“GFA”, “AvgHousePrice”]	2	0.3777	0.4133	5671.19
Forward	M3	[“GFA”, “AvgHousePrice”, “Length”]	3	0.3830	0.4359	5560.79
Forward	M4	[“GFA”, “AvgHousePrice”, “Length”, “AvgIncome”]	4	0.3884	0.4583	5448.97
Forward	M5	[“GFA”, “AvgHousePrice”, “Length”, “AvgIncome”, “PopDensity”]	5	0.4124	0.4963	5254.28
Backward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Backward	M2	[“GFA”, “AvgHousePrice”]	2	0.3777	0.4133	5671.19
Backward	M3	[“GFA”, “PopDensity”, “AvgHousePrice”]	3	0.3808	0.4338	5570.75
Backward	M4	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”]	4	0.3946	0.4638	5421.54
Backward	M5	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”]	5	0.4124	0.4963	5254.28
FS1 (Sweden)	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Forward	M1	[“Length”]	1	0.4269	0.4393	5293.42
Forward	M2	[“Length”, “GFA”]	2	0.4472	0.4712	5140.83
Forward	M3	[“Length”, “GFA”, “PopDensity”]	3	0.4391	0.4757	5119.02
Backward	M1	[“Length”]	1	0.4269	0.4393	5293.42
Backward	M2	[“GFA”, “Length”]	2	0.4472	0.4712	5140.83
Backward	M3	[“GFA”, “Length”, “PopDensity”]	3	0.4391	0.4757	5119.02
FS2 (Belgium)	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Forward	M2	[“GFA”, “Type_Other”]	2	0.3944	0.4290	5594.73
Forward	M3	[“GFA”, “Type_Other”, “AvgHousePrice”]	3	0.4073	0.4581	5450.15
Forward	M4	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”]	4	0.4252	0.4909	5282.46
Forward	M5	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”]	5	0.4400	0.5200	5129.62
Forward	M6	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”]	6	0.4567	0.5498	4967.39
Forward	M7	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”]	7	0.4600	0.5680	4866.33
Forward	M8	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”]	8	0.4663	0.5883	4750.53
Forward	M9	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”]	9	0.5107	0.6365	4463.47
Forward	M10	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”]	10	0.5045	0.6461	4404.67
Forward	M11	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”]	11	0.4978	0.6556	4344.66
Forward	M12	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”]	12	0.4833	0.6605	4314.10
Forward	M13	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”]	13	0.4616	0.6616	4307.16
Forward	M14	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZir”]	14	0.4364	0.6619	4305.21
Forward	M15	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZir”, “Length”]	15	0.4090	0.6623	4302.55
Forward	M16	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZir”, “Length”, “LU_AfZHabitat”]	16	0.3779	0.6623	4302.55
Backward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Backward	M2	[“GFA”, “Type_Offices”]	2	0.3639	0.4003	5733.56
Backward	M3	[“GFA”, “Type_Offices”, “Type_Residential”]	3	0.3714	0.4253	5612.71
Backward	M4	[“GFA”, “Type_Mixed”, “Type_Offices”, “Type_Residential”]	4	0.4490	0.5119	5172.35
Backward	M5	[“GFA”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”]	5	0.5053	0.5760	4820.90
Backward	M6	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”]	6	0.5197	0.6021	4670.47
Backward	M7	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”]	7	0.5312	0.6249	4534.24
Backward	M8	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZIndustrie”]	8	0.5281	0.6360	4466.93
Backward	M9	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZAdmin”, “LU_AfZIndustrie”]	9	0.5344	0.6541	4354.39
Backward	M10	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZAdmin”, “LU_AfZIndustrie”]	10	0.5239	0.6599	4317.63
Backward	M11	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	11	0.5057	0.6611	4310.30
Backward	M12	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	12	0.4849	0.6615	4307.60
Backward	M13	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	13	0.4621	0.6619	4305.21
Backward	M14	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	14	0.4371	0.6623	4302.57
Backward	M15	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	15	0.4090	0.6623	4302.55
Backward	M16	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	16	0.3779	0.6623	4302.55
FS2 (Sweden)	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Forward	M1	[“Type_Hospital”]	1	0.6340	0.6420	4229.98
Forward	M2	[“Type_Hospital”, “GFA”]	2	0.7266	0.7385	3615.34
Forward	M3	[“Type_Hospital”, “GFA”, “Type_Mixed”]	3	0.7259	0.7437	3578.77
Forward	M4	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”]	4	0.7229	0.7470	3555.92
Forward	M5	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”]	5	0.7170	0.7478	3550.52
Forward	M6	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”]	6	0.7106	0.7483	3546.66
Forward	M7	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”]	7	0.7035	0.7486	3544.67
Forward	M8	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”, “EC_Yes”]	8	0.6959	0.7488	3543.42
Backward	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Backward	M1	[“Type_Hospital”]	1	0.6340	0.6420	4229.98
Backward	M2	[“GFA”, “Type_Hospital”]	2	0.7266	0.7385	3615.34
Backward	M3	[“GFA”, “Type_Hospital”, “Type_Mixed”]	3	0.7259	0.7437	3578.77
Backward	M4	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”]	4	0.7229	0.7470	3555.92
Backward	M5	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	5	0.7170	0.7478	3550.52
Backward	M6	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	6	0.7106	0.7483	3546.66
Backward	M7	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”]	7	0.7035	0.7486	3544.67
Backward	M8	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “EC_Yes”]	8	0.6959	0.7488	3543.42
FS3 (Belgium)	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M1	[“Type_Other”]	1	0.4633	0.4787	5345.68
Forward	M2	[“Type_Other”, “GFA”]	2	0.5139	0.5417	5012.19
Forward	M3	[“Type_Other”, “GFA”, “AvgIncome”]	3	0.5498	0.5884	4749.88
Forward	M4	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”]	4	0.5632	0.6131	4604.95
Forward	M5	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”]	5	0.5806	0.6405	4438.98
Forward	M6	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”]	6	0.6057	0.6733	4231.68
Forward	M7	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”]	7	0.6102	0.6882	4134.34
Forward	M8	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”]	8	0.6085	0.6980	4068.68
Forward	M9	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”]	9	0.6697	0.7546	3667.36
Forward	M10	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”]	10	0.6677	0.7627	3606.85
Forward	M11	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”]	11	0.6668	0.7715	3538.98
Forward	M12	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”]	12	0.6614	0.7775	3492.35
Forward	M13	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”]	13	0.6551	0.7832	3447.20
Forward	M14	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”, “LU_AfZir”]	14	0.6393	0.7836	3444.22
Forward	M15	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”, “LU_AfZir”, “LU_AfZAdmin”]	15	0.6223	0.7842	3439.38
Forward	M16	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”, “LU_AfZir”, “LU_AfZAdmin”, “Length”]	16	0.6033	0.7847	3435.68
Backward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Backward	M2	[“GFA”, “Type_Mixed”]	2	0.4021	0.4363	5558.68
Backward	M3	[“GFA”, “Type_Mixed”, “Type_Offices”]	3	0.4432	0.4910	5282.36
Backward	M4	[“GFA”, “Type_Mixed”, “Type_Offices”, “Type_Residential”]	4	0.5474	0.5991	4687.82
Backward	M5	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Residential”]	5	0.5946	0.6525	4364.19
Backward	M6	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”]	6	0.6338	0.6966	4078.19
Backward	M7	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”]	7	0.6643	0.7315	3836.69
Backward	M8	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “EC_Yes”]	8	0.6715	0.7466	3727.01
Backward	M9	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZHabitat”, “EC_Yes”]	9	0.6790	0.7616	3615.26
Backward	M10	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “EC_Yes”]	10	0.6766	0.7690	3558.30
Backward	M11	[“GFA”, “PopDensity”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “EC_Yes”]	11	0.6689	0.7729	3527.92
Backward	M12	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “EC_Yes”]	12	0.6623	0.7781	3487.96
Backward	M13	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “LU_AfZIndustrie”, “EC_Yes”]	13	0.6551	0.7832	3447.20
Backward	M14	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZIndustrie”, “EC_Yes”]	14	0.6393	0.7836	3444.22
Backward	M15	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	15	0.6223	0.7842	3439.38
Backward	M16	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	16	0.6033	0.7847	3435.68
FS3 (Sweden)	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Forward	M1	[“Type_Hospital”]	1	0.7388	0.7444	3573.85
Forward	M2	[“Type_Hospital”, “GFA”]	2	0.8067	0.8151	3039.60
Forward	M3	[“Type_Hospital”, “GFA”, “Type_Mixed”]	3	0.8072	0.8197	3001.40
Forward	M4	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”]	4	0.8040	0.8210	2990.96
Forward	M5	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”]	5	0.8008	0.8225	2978.60
Forward	M6	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”]	6	0.7969	0.8234	2971.06
Forward	M7	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”]	7	0.7923	0.8239	2966.91
Forward	M8	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”, “EC_Yes”]	8	0.7872	0.8242	2964.30
Backward	M1	[“Type_Hospital”]	1	0.7388	0.7444	3573.85
Backward	M2	[“GFA”, “Type_Hospital”]	2	0.8067	0.8151	3039.60
Backward	M3	[“GFA”, “Type_Hospital”, “Type_Mixed”]	3	0.8072	0.8197	3001.40
Backward	M4	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”]	4	0.8040	0.8210	2990.96
Backward	M5	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	5	0.8008	0.8225	2978.60
Backward	M6	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	6	0.7969	0.8234	2971.06
Backward	M7	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”]	7	0.7923	0.8239	2966.91
Backward	M8	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “EC_Yes”]	8	0.7872	0.8242	2964.30

	Model	Features	#Features	MeanAR2	MeanR2	MeanRMSE
FS1 (Belgium)	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Forward	M2	[“GFA”, “AvgHousePrice”]	2	0.3777	0.4133	5671.19
Forward	M3	[“GFA”, “AvgHousePrice”, “Length”]	3	0.3830	0.4359	5560.79
Forward	M4	[“GFA”, “AvgHousePrice”, “Length”, “AvgIncome”]	4	0.3884	0.4583	5448.97
Forward	M5	[“GFA”, “AvgHousePrice”, “Length”, “AvgIncome”, “PopDensity”]	5	0.4124	0.4963	5254.28
Backward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Backward	M2	[“GFA”, “AvgHousePrice”]	2	0.3777	0.4133	5671.19
Backward	M3	[“GFA”, “PopDensity”, “AvgHousePrice”]	3	0.3808	0.4338	5570.75
Backward	M4	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”]	4	0.3946	0.4638	5421.54
Backward	M5	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”]	5	0.4124	0.4963	5254.28
FS1 (Sweden)	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Forward	M1	[“Length”]	1	0.4269	0.4393	5293.42
Forward	M2	[“Length”, “GFA”]	2	0.4472	0.4712	5140.83
Forward	M3	[“Length”, “GFA”, “PopDensity”]	3	0.4391	0.4757	5119.02
Backward	M1	[“Length”]	1	0.4269	0.4393	5293.42
Backward	M2	[“GFA”, “Length”]	2	0.4472	0.4712	5140.83
Backward	M3	[“GFA”, “Length”, “PopDensity”]	3	0.4391	0.4757	5119.02
FS2 (Belgium)	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Forward	M2	[“GFA”, “Type_Other”]	2	0.3944	0.4290	5594.73
Forward	M3	[“GFA”, “Type_Other”, “AvgHousePrice”]	3	0.4073	0.4581	5450.15
Forward	M4	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”]	4	0.4252	0.4909	5282.46
Forward	M5	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”]	5	0.4400	0.5200	5129.62
Forward	M6	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”]	6	0.4567	0.5498	4967.39
Forward	M7	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”]	7	0.4600	0.5680	4866.33
Forward	M8	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”]	8	0.4663	0.5883	4750.53
Forward	M9	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”]	9	0.5107	0.6365	4463.47
Forward	M10	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”]	10	0.5045	0.6461	4404.67
Forward	M11	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”]	11	0.4978	0.6556	4344.66
Forward	M12	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”]	12	0.4833	0.6605	4314.10
Forward	M13	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”]	13	0.4616	0.6616	4307.16
Forward	M14	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZir”]	14	0.4364	0.6619	4305.21
Forward	M15	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZir”, “Length”]	15	0.4090	0.6623	4302.55
Forward	M16	[“GFA”, “Type_Other”, “AvgHousePrice”, “LU_AfZFMixite”, “Type_Residential”, “AvgIncome”, “PopDensity”, “Type_Offices”, “Type_Mixed”, “LU_AfZIndustrie”, “LU_AfZAdmin”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZir”, “Length”, “LU_AfZHabitat”]	16	0.3779	0.6623	4302.55
Backward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Backward	M2	[“GFA”, “Type_Offices”]	2	0.3639	0.4003	5733.56
Backward	M3	[“GFA”, “Type_Offices”, “Type_Residential”]	3	0.3714	0.4253	5612.71
Backward	M4	[“GFA”, “Type_Mixed”, “Type_Offices”, “Type_Residential”]	4	0.4490	0.5119	5172.35
Backward	M5	[“GFA”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”]	5	0.5053	0.5760	4820.90
Backward	M6	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”]	6	0.5197	0.6021	4670.47
Backward	M7	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”]	7	0.5312	0.6249	4534.24
Backward	M8	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZIndustrie”]	8	0.5281	0.6360	4466.93
Backward	M9	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZAdmin”, “LU_AfZIndustrie”]	9	0.5344	0.6541	4354.39
Backward	M10	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZAdmin”, “LU_AfZIndustrie”]	10	0.5239	0.6599	4317.63
Backward	M11	[“GFA”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	11	0.5057	0.6611	4310.30
Backward	M12	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	12	0.4849	0.6615	4307.60
Backward	M13	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	13	0.4621	0.6619	4305.21
Backward	M14	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	14	0.4371	0.6623	4302.57
Backward	M15	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	15	0.4090	0.6623	4302.55
Backward	M16	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	16	0.3779	0.6623	4302.55
FS2 (Sweden)	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Forward	M1	[“Type_Hospital”]	1	0.6340	0.6420	4229.98
Forward	M2	[“Type_Hospital”, “GFA”]	2	0.7266	0.7385	3615.34
Forward	M3	[“Type_Hospital”, “GFA”, “Type_Mixed”]	3	0.7259	0.7437	3578.77
Forward	M4	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”]	4	0.7229	0.7470	3555.92
Forward	M5	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”]	5	0.7170	0.7478	3550.52
Forward	M6	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”]	6	0.7106	0.7483	3546.66
Forward	M7	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”]	7	0.7035	0.7486	3544.67
Forward	M8	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”, “EC_Yes”]	8	0.6959	0.7488	3543.42
Backward	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Backward	M1	[“Type_Hospital”]	1	0.6340	0.6420	4229.98
Backward	M2	[“GFA”, “Type_Hospital”]	2	0.7266	0.7385	3615.34
Backward	M3	[“GFA”, “Type_Hospital”, “Type_Mixed”]	3	0.7259	0.7437	3578.77
Backward	M4	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”]	4	0.7229	0.7470	3555.92
Backward	M5	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	5	0.7170	0.7478	3550.52
Backward	M6	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	6	0.7106	0.7483	3546.66
Backward	M7	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”]	7	0.7035	0.7486	3544.67
Backward	M8	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “EC_Yes”]	8	0.6959	0.7488	3543.42
FS3 (Belgium)	M0	Mean Transport Model	0	0.0000	0.0000	7403.69
Forward	M1	[“Type_Other”]	1	0.4633	0.4787	5345.68
Forward	M2	[“Type_Other”, “GFA”]	2	0.5139	0.5417	5012.19
Forward	M3	[“Type_Other”, “GFA”, “AvgIncome”]	3	0.5498	0.5884	4749.88
Forward	M4	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”]	4	0.5632	0.6131	4604.95
Forward	M5	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”]	5	0.5806	0.6405	4438.98
Forward	M6	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”]	6	0.6057	0.6733	4231.68
Forward	M7	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”]	7	0.6102	0.6882	4134.34
Forward	M8	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”]	8	0.6085	0.6980	4068.68
Forward	M9	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”]	9	0.6697	0.7546	3667.36
Forward	M10	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”]	10	0.6677	0.7627	3606.85
Forward	M11	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”]	11	0.6668	0.7715	3538.98
Forward	M12	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”]	12	0.6614	0.7775	3492.35
Forward	M13	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”]	13	0.6551	0.7832	3447.20
Forward	M14	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”, “LU_AfZir”]	14	0.6393	0.7836	3444.22
Forward	M15	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”, “LU_AfZir”, “LU_AfZAdmin”]	15	0.6223	0.7842	3439.38
Forward	M16	[“Type_Other”, “GFA”, “AvgIncome”, “PopDensity”, “LU_AfZFMixite”, “AvgHousePrice”, “Type_Residential”, “Type_Mixed”, “Type_Offices”, “LU_AfZIndustrie”, “LU_AfZTransPort”, “EC_Yes”, “LU_AfZHabitat”, “LU_AfZir”, “LU_AfZAdmin”, “Length”]	16	0.6033	0.7847	3435.68
Backward	M1	[“GFA”]	1	0.3524	0.3709	5872.50
Backward	M2	[“GFA”, “Type_Mixed”]	2	0.4021	0.4363	5558.68
Backward	M3	[“GFA”, “Type_Mixed”, “Type_Offices”]	3	0.4432	0.4910	5282.36
Backward	M4	[“GFA”, “Type_Mixed”, “Type_Offices”, “Type_Residential”]	4	0.5474	0.5991	4687.82
Backward	M5	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Residential”]	5	0.5946	0.6525	4364.19
Backward	M6	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”]	6	0.6338	0.6966	4078.19
Backward	M7	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”]	7	0.6643	0.7315	3836.69
Backward	M8	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “EC_Yes”]	8	0.6715	0.7466	3727.01
Backward	M9	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZHabitat”, “EC_Yes”]	9	0.6790	0.7616	3615.26
Backward	M10	[“GFA”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “EC_Yes”]	10	0.6766	0.7690	3558.30
Backward	M11	[“GFA”, “PopDensity”, “AvgIncome”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “EC_Yes”]	11	0.6689	0.7729	3527.92
Backward	M12	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “EC_Yes”]	12	0.6623	0.7781	3487.96
Backward	M13	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZHabitat”, “LU_AfZIndustrie”, “EC_Yes”]	13	0.6551	0.7832	3447.20
Backward	M14	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZIndustrie”, “EC_Yes”]	14	0.6393	0.7836	3444.22
Backward	M15	[“GFA”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	15	0.6223	0.7842	3439.38
Backward	M16	[“GFA”, “Length”, “PopDensity”, “AvgIncome”, “AvgHousePrice”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “Type_Residential”, “LU_AfZFMixite”, “LU_AfZTransPort”, “LU_AfZir”, “LU_AfZHabitat”, “LU_AfZAdmin”, “LU_AfZIndustrie”, “EC_Yes”]	16	0.6033	0.7847	3435.68
FS3 (Sweden)	M0	Mean Transport Model	0	0.0000	0.0000	7069.43
Forward	M1	[“Type_Hospital”]	1	0.7388	0.7444	3573.85
Forward	M2	[“Type_Hospital”, “GFA”]	2	0.8067	0.8151	3039.60
Forward	M3	[“Type_Hospital”, “GFA”, “Type_Mixed”]	3	0.8072	0.8197	3001.40
Forward	M4	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”]	4	0.8040	0.8210	2990.96
Forward	M5	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”]	5	0.8008	0.8225	2978.60
Forward	M6	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”]	6	0.7969	0.8234	2971.06
Forward	M7	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”]	7	0.7923	0.8239	2966.91
Forward	M8	[“Type_Hospital”, “GFA”, “Type_Mixed”, “Length”, “Type_Offices”, “PopDensity”, “Type_Other”, “EC_Yes”]	8	0.7872	0.8242	2964.30
Backward	M1	[“Type_Hospital”]	1	0.7388	0.7444	3573.85
Backward	M2	[“GFA”, “Type_Hospital”]	2	0.8067	0.8151	3039.60
Backward	M3	[“GFA”, “Type_Hospital”, “Type_Mixed”]	3	0.8072	0.8197	3001.40
Backward	M4	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”]	4	0.8040	0.8210	2990.96
Backward	M5	[“GFA”, “Length”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	5	0.8008	0.8225	2978.60
Backward	M6	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”]	6	0.7969	0.8234	2971.06
Backward	M7	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”]	7	0.7923	0.8239	2966.91
Backward	M8	[“GFA”, “Length”, “PopDensity”, “Type_Hospital”, “Type_Mixed”, “Type_Offices”, “Type_Other”, “EC_Yes”]	8	0.7872	0.8242	2964.30

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