The Insurance Company benchmark (COIL 2000) dataset

1: Description.

This data set used in the CoIL 2000 Challenge contains information on customers of an insurance company. The data consists of 86 variables and includes product usage data and socio-demographic data. 

2: Type.			Regression
3: Origin.			Real world
4: Instances.		9822
5: Features.		85
6: Missing values.	No

7: Header.
@relation tic
@attribute MOSTYPE integer [1, 41]
@attribute MAANTHUI integer [1, 10]
@attribute MGEMOMV integer [1, 6]
@attribute MGEMLEEF integer [1, 6]
@attribute MOSHOOFD integer [1, 10]
@attribute MGODRK integer [0, 9]
@attribute MGODPR integer [0, 9]
@attribute MGODOV integer [0, 5]
@attribute MGODGE integer [0, 9]
@attribute MRELGE integer [0, 9]
@attribute MRELSA integer [0, 7]
@attribute MRELOV integer [0, 9]
@attribute MFALLEEN integer [0, 9]
@attribute MFGEKIND integer [0, 9]
@attribute MFWEKIND integer [0, 9]
@attribute MOPLHOOG integer [0, 9]
@attribute MOPLMIDD integer [0, 9]
@attribute MOPLLAAG integer [0, 9]
@attribute MBERHOOG integer [0, 9]
@attribute MBERZELF integer [0, 5]
@attribute MBERBOER integer [0, 9]
@attribute MBERMIDD integer [0, 9]
@attribute MBERARBG integer [0, 9]
@attribute MBERARBO integer [0, 9]
@attribute MSKA integer [0, 9]
@attribute MSKB1 integer [0, 9]
@attribute MSKB2 integer [0, 9]
@attribute MSKC integer [0, 9]
@attribute MSKD integer [0, 9]
@attribute MHHUUR integer [0, 9]
@attribute MHKOOP integer [0, 9]
@attribute MAUT1 integer [0, 9]
@attribute MAUT2 integer [0, 9]
@attribute MAUT0 integer [0, 9]
@attribute MZFONDS integer [0, 9]
@attribute MZPART integer [0, 9]
@attribute MINKM30 integer [0, 9]
@attribute MINK3045 integer [0, 9]
@attribute MINK4575 integer [0, 9]
@attribute MINK7512 integer [0, 9]
@attribute MINK123M integer [0, 9]
@attribute MINKGEM integer [0, 9]
@attribute MKOOPKLA integer [1, 8]
@attribute PWAPART integer [0, 3]
@attribute PWABEDR integer [0, 6]
@attribute PWALAND integer [0, 4]
@attribute PPERSAUT integer [0, 9]
@attribute PBESAUT integer [0, 7]
@attribute PMOTSCO integer [0, 7]
@attribute PVRAAUT integer [0, 9]
@attribute PAANHANG integer [0, 5]
@attribute PTRACTOR integer [0, 7]
@attribute PWERKT integer [0, 6]
@attribute PBROM integer [0, 6]
@attribute PLEVEN integer [0, 9]
@attribute PPERSONG integer [0, 6]
@attribute PGEZONG integer [0, 3]
@attribute PWAOREG integer [0, 7]
@attribute PBRAND integer [0, 8]
@attribute PZEILPL integer [0, 3]
@attribute PPLEZIER integer [0, 6]
@attribute PFIETS integer [0, 1]
@attribute PINBOED integer [0, 6]
@attribute PBYSTAND integer [0, 5]
@attribute AWAPART integer [0, 2]
@attribute AWABEDR integer [0, 5]
@attribute AWALAND integer [0, 1]
@attribute APERSAUT integer [0, 12]
@attribute ABESAUT integer [0, 5]
@attribute AMOTSCO integer [0, 8]
@attribute AVRAAUT integer [0, 4]
@attribute AAANHANG integer [0, 3]
@attribute ATRACTOR integer [0, 6]
@attribute AWERKT integer [0, 6]
@attribute ABROM integer [0, 3]
@attribute ALEVEN integer [0, 8]
@attribute APERSONG integer [0, 1]
@attribute AGEZONG integer [0, 1]
@attribute AWAOREG integer [0, 2]
@attribute ABRAND integer [0, 7]
@attribute AZEILPL integer [0, 1]
@attribute APLEZIER integer [0, 2]
@attribute AFIETS integer [0, 4]
@attribute AINBOED integer [0, 2]
@attribute ABYSTAND integer [0, 2]
@attribute CARAVAN integer [0, 1]
@inputs MOSTYPE, MAANTHUI, MGEMOMV, MGEMLEEF, MOSHOOFD, MGODRK, MGODPR, MGODOV, MGODGE, MRELGE, MRELSA, MRELOV, MFALLEEN, MFGEKIND, MFWEKIND, MOPLHOOG, MOPLMIDD, MOPLLAAG, MBERHOOG, MBERZELF, MBERBOER, MBERMIDD, MBERARBG, MBERARBO, MSKA, MSKB1, MSKB2, MSKC, MSKD, MHHUUR, MHKOOP, MAUT1, MAUT2, MAUT0, MZFONDS, MZPART, MINKM30, MINK3045, MINK4575, MINK7512, MINK123M, MINKGEM, MKOOPKLA, PWAPART, PWABEDR, PWALAND, PPERSAUT, PBESAUT, PMOTSCO, PVRAAUT, PAANHANG, PTRACTOR, PWERKT, PBROM, PLEVEN, PPERSONG, PGEZONG, PWAOREG, PBRAND, PZEILPL, PPLEZIER, PFIETS, PINBOED, PBYSTAND, AWAPART, AWABEDR, AWALAND, APERSAUT, ABESAUT, AMOTSCO, AVRAAUT, AAANHANG, ATRACTOR, AWERKT, ABROM, ALEVEN, APERSONG, AGEZONG, AWAOREG, ABRAND, AZEILPL, APLEZIER, AFIETS, AINBOED, ABYSTAND
@outputs CARAVAN

DATA DICTIONARY

Nr Name Description Domain
1 MOSTYPE Customer Subtype see L0
2 MAANTHUI Number of houses 1 – 10
3 MGEMOMV Avg size household 1 – 6
4 MGEMLEEF Avg age see L1
5 MOSHOOFD Customer main type see L2
6 MGODRK Roman catholic see L3
7 MGODPR Protestant ...
8 MGODOV Other religion
9 MGODGE No religion
10 MRELGE Married
11 MRELSA Living together
12 MRELOV Other relation
13 MFALLEEN Singles
14 MFGEKIND Household without children
15 MFWEKIND Household with children
16 MOPLHOOG High level education
17 MOPLMIDD Medium level education
18 MOPLLAAG Lower level education
19 MBERHOOG High status
20 MBERZELF Entrepreneur
21 MBERBOER Farmer
22 MBERMIDD Middle management
23 MBERARBG Skilled labourers
24 MBERARBO Unskilled labourers
25 MSKA Social class A
26 MSKB1 Social class B1
27 MSKB2 Social class B2
28 MSKC Social class C
29 MSKD Social class D
30 MHHUUR Rented house
31 MHKOOP Home owners
32 MAUT1 1 car
33 MAUT2 2 cars
34 MAUT0 No car
35 MZFONDS National Health Service
36 MZPART Private health insurance
37 MINKM30 Income < 30.000
38 MINK3045 Income 30-45.000
39 MINK4575 Income 45-75.000
40 MINK7512 Income 75-122.000
41 MINK123M Income >123.000
42 MINKGEM Average income
43 MKOOPKLA Purchasing power class
44 PWAPART Contribution private third party insurance see L4
45 PWABEDR Contribution third party insurance (firms) ...
46 PWALAND Contribution third party insurane (agriculture)
47 PPERSAUT Contribution car policies
48 PBESAUT Contribution delivery van policies
49 PMOTSCO Contribution motorcycle/scooter policies
50 PVRAAUT Contribution lorry policies
51 PAANHANG Contribution trailer policies
52 PTRACTOR Contribution tractor policies
53 PWERKT Contribution agricultural machines policies 
54 PBROM Contribution moped policies
55 PLEVEN Contribution life insurances
56 PPERSONG Contribution private accident insurance policies
57 PGEZONG Contribution family accidents insurance policies
58 PWAOREG Contribution disability insurance policies
59 PBRAND Contribution fire policies
60 PZEILPL Contribution surfboard policies
61 PPLEZIER Contribution boat policies
62 PFIETS Contribution bicycle policies
63 PINBOED Contribution property insurance policies
64 PBYSTAND Contribution social security insurance policies
65 AWAPART Number of private third party insurance 1 - 12
66 AWABEDR Number of third party insurance (firms) ...
67 AWALAND Number of third party insurane (agriculture)
68 APERSAUT Number of car policies
69 ABESAUT Number of delivery van policies
70 AMOTSCO Number of motorcycle/scooter policies
71 AVRAAUT Number of lorry policies
72 AAANHANG Number of trailer policies
73 ATRACTOR Number of tractor policies
74 AWERKT Number of agricultural machines policies
75 ABROM Number of moped policies
76 ALEVEN Number of life insurances
77 APERSONG Number of private accident insurance policies
78 AGEZONG Number of family accidents insurance policies
79 AWAOREG Number of disability insurance policies
80 ABRAND Number of fire policies
81 AZEILPL Number of surfboard policies
82 APLEZIER Number of boat policies
83 AFIETS Number of bicycle policies
84 AINBOED Number of property insurance policies
85 ABYSTAND Number of social security insurance policies
86 CARAVAN Number of mobile home policies 0 - 1


L0:

Value Label
1 High Income, expensive child
2 Very Important Provincials
3 High status seniors
4 Affluent senior apartments
5 Mixed seniors
6 Career and childcare
7 Dinki's (double income no kids)
8 Middle class families
9 Modern, complete families
10 Stable family
11 Family starters
12 Affluent young families
13 Young all american family
14 Junior cosmopolitan
15 Senior cosmopolitans
16 Students in apartments
17 Fresh masters in the city
18 Single youth
19 Suburban youth
20 Etnically diverse
21 Young urban have-nots
22 Mixed apartment dwellers
23 Young and rising
24 Young, low educated 
25 Young seniors in the city
26 Own home elderly
27 Seniors in apartments
28 Residential elderly
29 Porchless seniors: no front yard
30 Religious elderly singles
31 Low income catholics
32 Mixed seniors
33 Lower class large families
34 Large family, employed child
35 Village families
36 Couples with teens 'Married with children'
37 Mixed small town dwellers
38 Traditional families
39 Large religous families
40 Large family farms
41 Mixed rurals


L1:

1 20-30 years
2 30-40 years
3 40-50 years
4 50-60 years
5 60-70 years
6 70-80 years


L2:

1 Successful hedonists
2 Driven Growers
3 Average Family
4 Career Loners
5 Living well
6 Cruising Seniors
7 Retired and Religeous
8 Family with grown ups
9 Conservative families
10 Farmers


L3:

0 0%
1 1 - 10%
2 11 - 23%
3 24 - 36%
4 37 - 49%
5 50 - 62%
6 63 - 75%
7 76 - 88%
8 89 - 99%
9 100%


L4:

0 f 0
1 f 1 – 49
2 f 50 – 99
3 f 100 – 199
4 f 200 – 499
5 f 500 – 999
6 f 1000 – 4999
7 f 5000 – 9999
8 f 10.000 - 19.999
9 f 20.000 - ?