ticdata: The Insurance Company Data

In kernlab: Kernel-Based Machine Learning Lab

The Insurance Company Data

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 derived from zip area codes. The data was collected to answer the following question: Can you predict who would be interested in buying a caravan insurance policy and give an explanation why ?

Usage

data(ticdata)

Format

ticdata: Dataset to train and validate prediction models and build a description (9822 customer records). Each record consists of 86 attributes, containing sociodemographic data (attribute 1-43) and product ownership (attributes 44-86). The sociodemographic data is derived from zip codes. All customers living in areas with the same zip code have the same sociodemographic attributes. Attribute 86, CARAVAN:Number of mobile home policies, is the target variable.

Data Format

	1	STYPE	Customer Subtype
	2	MAANTHUI	Number of houses 1 - 10
	3	MGEMOMV	Avg size household 1 - 6
	4	MGEMLEEF	Average age
	5	MOSHOOFD	Customer main type
	6	MGODRK	Roman catholic
	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
	45	PWABEDR	Contribution third party insurance (firms)
	46	PWALAND	Contribution third party insurance (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 insurance (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

Note: All the variables starting with M are zipcode variables. They give information on the distribution of that variable, e.g., Rented house, in the zipcode area of the customer.

Details

Information about the insurance company customers consists of 86 variables and includes product usage data and socio-demographic data derived from zip area codes. The data was supplied by the Dutch data mining company Sentient Machine Research and is based on a real world business problem. The training set contains over 5000 descriptions of customers, including the information of whether or not they have a caravan insurance policy. The test set contains 4000 customers. The test and data set are merged in the ticdata set. More information about the data set and the CoIL 2000 Challenge along with publications based on the data set can be found at http://www.liacs.nl/~putten/library/cc2000/.

Source

• UCI KDD Archive:http://kdd.ics.uci.edu

• Donor: Sentient Machine Research
  Peter van der Putten
  Sentient Machine Research
  Baarsjesweg 224
  1058 AA Amsterdam
  The Netherlands
  [phone]
  [e-mail], [e-mail]

References

Peter van der Putten, Michel de Ruiter, Maarten van Someren CoIL Challenge 2000 Tasks and Results: Predicting and Explaining Caravan Policy Ownership
http://www.liacs.nl/~putten/library/cc2000/

kernlab documentation built on Sept. 12, 2024, 6:51 a.m.