auto_claim: Automotive claims
In sdcastillo/ExamPAData: Data Sets for Predictive Analytics Exam

auto_claim

R Documentation

Automotive claims

Description

Automotive claims

Usage

auto_claim

Format

data.frame, 10296 observations of 29 variables:

POLICYNO: Policy number.
PLCYDATE: Date that policy was signed.
CLM_FREQ5: Number of claims.
CLM_AMT5: Aggregate claim loss of policy (in thousands).
CLM_AMT
KIDSDRIV: Number of child passengers.
TRAVTIME: Time to commute.
CAR_USE: (1) Private or (2) commercial use.
BLUEBOOK: (log) car value.
RETAINED: Whether the policy was retained or not.
NPOLICY: Number of policies.
CAR_TYPE: (0-1 dummy variables) Type of car : (base) Panel Truck, (2) Pickup,(3) Sedan, (4) Sports Car, (5) SUV, (6) Van
RED_CAR: Whether the color of the car is (2) car or (1) not.
REVOLKED: Whether the policyholder's license was (2) revoked in the past or (1) not.
MVR_PTS: Number of motor vehicle record points.
CLM_FLAG: Whether there was a claim or not.
AGE: Age.
HOMEKIDS: Number of children at home.
YOJ: Year of job.
INCOME: Annual income.
GENDER: Gender of policyholder : (1) female or (2) male.
MARRIED: Whether the policyholder is (2) married or (1) not.
PARENT1: Whether (2) the policyholder grew up in a single-parent family or (1) not.
JOBCLASS: (0-1 dummy variables) Job class of policyholder: (base) Unknown, (2) Blue Collar, (3) Clerical, (4) Doctor, (5) Home Maker, (6) Lawyer, (7) Manager, (8) Professional, (9) Student
MAX_EDUC: (0-1 dummy variables) Maximal level of education of policyholder: (base) less than High School, (2) Bachelors, (3) High School, (4) Masters, (5) PhD.
HOME_VAL: Value of home.
SAMEHOME: Whether they grew up in the same home as their current home.
AREA: (1) Rural or (2) urban area.
IN_YY: Year.