insurance

0th

Percentile

Insurance Dataset

Dataset of car-insurance customers from Belgium in 1992

Keywords
datasets
Details

Dataset for DISQUAL method

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

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

Aliases
  • insurance
Examples
## Not run: 
#   # load data
#   data(insurance)
# 
#   # structure
#   str(insurance)
#  ## End(Not run)
Documentation reproduced from package DiscriMiner, version 0.1-29, License: GPL-3

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