DiscriMiner (version 0.1-29)

insurance: Insurance Dataset

Description

Dataset of car-insurance customers from Belgium in 1992

Format

A data frame with 1106 observations on the following 10 variables.

Claims

Group variable. A factor with levels bad and good

Use

Type of Use. A factor with levels private and professional

Type

Insurance Type. A factor with levels companies, female, and male

Language

Language. A factor with levels flemish and french

BirthCohort

Birth Cohort. A factor with levels BD_1890_1949, BD_1950_1973, and BD_unknown

Region

Geographic Region. A factor with levels Brussels and Other_regions

BonusMalus

Level of bonus-malus. A factor with levels BM_minus and BM_plus

YearSuscrip

Year of Subscription. A factor with levels YS<86< code=""> and YS>=86

Horsepower

Horsepower. A factor with levels HP<=39< code=""> and HP>=40

YearConstruc

Year of vehicle construction. A factor with levels YC_33_89 and YC_90_91

Details

Dataset for DISQUAL method

References

Saporta G., Niang N. (2006) Correspondence Analysis and Classification. In Multiple Correspondence Analysis and Related Methods, M. Greenacre and J. Blasius, Eds., pp 371-392. Chapman & Hall/CRC, Boca Raton, Florida, USA.

See Also

disqual

Examples

## Not run: 
#   # load data
#   data(insurance)
# 
#   # structure
#   str(insurance)
#  ## End(Not run)