Donated on 5/18/1987

From 1985 Ward's Automotive Yearbook

Dataset Characteristics


Subject Area


Associated Tasks


Feature Type

Categorical, Integer, Real

# Instances


# Features


Dataset Information

Additional Information

This data set consists of three types of entities: (a) the specification of an auto in terms of various characteristics, (b) its assigned insurance risk rating, (c) its normalized losses in use as compared to other cars. The second rating corresponds to the degree to which the auto is more risky than its price indicates. Cars are initially assigned a risk factor symbol associated with its price. Then, if it is more risky (or less), this symbol is adjusted by moving it up (or down) the scale. Actuarians call this process "symboling". A value of +3 indicates that the auto is risky, -3 that it is probably pretty safe. The third factor is the relative average loss payment per insured vehicle year. This value is normalized for all autos within a particular size classification (two-door small, station wagons, sports/speciality, etc...), and represents the average loss per car per year. Note: Several of the attributes in the database could be used as a "class" attribute.

Has Missing Values?


Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
priceFeatureContinuouscontinuous from 5118 to 45400yes
highway-mpgFeatureContinuouscontinuous from 16 to 54no
city-mpgFeatureContinuouscontinuous from 13 to 49no
peak-rpmFeatureContinuouscontinuous from 4150 to 6600yes
horsepowerFeatureContinuouscontinuous from 48 to 288yes
compression-ratioFeatureContinuouscontinuous from 7 to 23no
strokeFeatureContinuouscontinuous from 2.07 to 4.17yes
boreFeatureContinuouscontinuous from 2.54 to 3.94yes
fuel-systemFeatureCategorical1bbl, 2bbl, 4bbl, idi, mfi, mpfi, spdi, spfino
engine-sizeFeatureContinuouscontinuous from 61 to 326no

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Additional Variable Information

Attribute: Attribute Range 1. symboling: -3, -2, -1, 0, 1, 2, 3. 2. normalized-losses: continuous from 65 to 256. 3. make: alfa-romero, audi, bmw, chevrolet, dodge, honda, isuzu, jaguar, mazda, mercedes-benz, mercury, mitsubishi, nissan, peugot, plymouth, porsche, renault, saab, subaru, toyota, volkswagen, volvo 4. fuel-type: diesel, gas. 5. aspiration: std, turbo. 6. num-of-doors: four, two. 7. body-style: hardtop, wagon, sedan, hatchback, convertible. 8. drive-wheels: 4wd, fwd, rwd. 9. engine-location: front, rear. 10. wheel-base: continuous from 86.6 120.9. 11. length: continuous from 141.1 to 208.1. 12. width: continuous from 60.3 to 72.3. 13. height: continuous from 47.8 to 59.8. 14. curb-weight: continuous from 1488 to 4066. 15. engine-type: dohc, dohcv, l, ohc, ohcf, ohcv, rotor. 16. num-of-cylinders: eight, five, four, six, three, twelve, two. 17. engine-size: continuous from 61 to 326. 18. fuel-system: 1bbl, 2bbl, 4bbl, idi, mfi, mpfi, spdi, spfi. 19. bore: continuous from 2.54 to 3.94. 20. stroke: continuous from 2.07 to 4.17. 21. compression-ratio: continuous from 7 to 23. 22. horsepower: continuous from 48 to 288. 23. peak-rpm: continuous from 4150 to 6600. 24. city-mpg: continuous from 13 to 49. 25. highway-mpg: continuous from 16 to 54. 26. price: continuous from 5118 to 45400.

Baseline Model Performance

Papers Citing this Dataset

Spectral ranking and unsupervised feature selection for point, collective, and contextual anomaly detection

By Haofan Zhang, Ke Nian, Thomas Coleman, Yuying Li. 2018

Published in International Journal of Data Science and Analytics.

Improving the interpretability of classification rules discovered by an ant colony algorithm

By Fernando Otero, Alex Freitas. 2013

Published in GECCO '13.

A study of different quality evaluation functions in the cAnt-Miner(PB) classification algorithm

By Matthew Medland, Fernando Otero. 2012

Published in GECCO '12.

Integration of Data Mining and Data Warehousing: A Practical Methodology

By Muhammad Usman, Russel Pears. 2010

Published in Int. J. Adv. Comp. Techn..

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8 citations




Jeffrey Schlimmer


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