insurance_dataset
OpenML dataset with id 43157
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22101752/insurance_dataset.arff
Upload date: 31 January 2022
Dataset Characteristics
Number of features: 27 (numeric: 0, symbolic: 27 and in total binary: 8 )
Number of instances: 20,000
Number of instances with missing values: 0
Number of missing values: 0
Dataset description
Insurance is a network for evaluating car insurance risks.
Format of the dataset
The insurance data set contains the following 27 variables:
GoodStudent (good student): a two-level factor with levels False and True.
Age (age): a three-level factor with levels Adolescent, Adult and Senior.
SocioEcon (socio-economic status): a four-level factor with levels Prole, Middle, UpperMiddle and Wealthy.
RiskAversion (risk aversion): a four-level factor with levels Psychopath, Adventurous, Normal and Cautious.
VehicleYear (vehicle age): a two-level factor with levels Current and older.
ThisCarDam (damage to this car): a four-level factor with levels None, Mild, Moderate and Severe.
RuggedAuto (ruggedness of the car): a three-level factor with levels EggShell, Football and Tank.
Accident (severity of the accident): a four-level factor with levels None, Mild, Moderate and Severe.
MakeModel (car's model): a five-level factor with levels SportsCar, Economy, FamilySedan, Luxury and SuperLuxury.
DrivQuality (driving quality): a three-level factor with levels Poor, Normal and Excellent.
Mileage (mileage): a four-level factor with levels FiveThou, TwentyThou, FiftyThou and Domino.
Antilock (ABS): a two-level factor with levels False and True.
DrivingSkill (driving skill): a three-level factor with levels SubStandard, Normal and Expert.
SeniorTrain (senior training): a two-level factor with levels False and True.
ThisCarCost (costs for the insured car): a four-level factor with levels Thousand, TenThou, HundredThou and Million.
Theft (theft): a two-level factor with levels False and True.
CarValue (value of the car): a five-level factor with levels FiveThou, TenThou, TwentyThou, FiftyThou and Million.
HomeBase (neighbourhood type): a four-level factor with levels Secure, City, Suburb and Rural.
AntiTheft (anti-theft system): a two-level factor with levels False and True.
PropCost (ratio of the cost for the two cars): a four-level factor with levels Thousand, TenThou, HundredThou and Million.
OtherCarCost (costs for the other car): a four-level factor with levels Thousand, TenThou, HundredThou and Million.
OtherCar (other cars involved in the accident): a two-level factor with levels False and True.
MedCost (cost of the medical treatment): a four-level factor with levels Thousand, TenThou, HundredThou and Million.
Cushioning (cushioning): a four-level factor with levels Poor, Fair, Good and Excellent.
Airbag (airbag): a two-level factor with levels False and True.
ILiCost (inspection cost): a four-level factor with levels Thousand, TenThou, HundredThou and Million.
DrivHist (driving history): a three-level factor with levels Zero, One and Many.
Source
Binder J, Koller D, Russell S, Kanazawa K (1997). "Adaptive Probabilistic Networks with Hidden Variables". Machine Learning, 29(2-3):213-244.
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