auto: Automobile data

In GSE: Robust Estimation in the Presence of Cellwise and Casewise Contamination and Missing Data

Automobile data

Description

This data set is taken from UCI repository, see reference. Past usage includes price prediction of cars using all numeric and boolean attributes (Kibler et al., 1989).

Usage

data(auto)

Format

A data frame with 205 observations on the following 26 variables, of which 15 are quantitative and 11 are categorical. The following description is extracted from UCI repository (Frank and Asuncion, 2010):

Normalized-losses	the relative average loss payment per insured vehicle year; ranged from 65 to 256
Make	Vehicle's make
Fuel-type	diesel, gas
Aspiration	std, turbo
Num-of-doors	four, two
Body-style	hardtop, wagon, sedan, hatchback, convertible
Drive-wheels	4wd, fwd, rwd
Engine-location	front, rear
Wheel-base	continuous from 86.6 120.9
Length	continuous from 141.1 to 208.1
Width	continuous from 60.3 to 72.3
Height	continuous from 47.8 to 59.8
Curb-weight	continuous from 1488 to 4066
Engine-type	dohc, dohcv, l, ohc, ohcf, ohcv, rotor
Num-of-cylinders	eight, five, four, six, three, twelve, two
Engine-size	continuous from 61 to 326
Fuel-system	1bbl, 2bbl, 4bbl, idi, mfi, mpfi, spdi, spfi
Bore	continuous from 2.54 to 3.94
Stroke	continuous from 2.07 to 4.17
Compression-ratio	continuous from 7 to 23
Horsepower	continuous from 48 to 288
Peak-rpm	continuous from 4150 to 6600
City-mpg	continuous from 13 to 49
Highway-mpg	continuous from 16 to 54
Price	continuous from 5118 to 45400
Symboling	assigned insurance risk rating: -3, -2, -1, 0, 1, 2, 3

Source

The original data have been taken from the UCI Repository Of Machine Learning Databases at

• http://archive.ics.uci.edu/ml/datasets/Automobile.

References

Frank, A. & Asuncion, A. (2010). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Kibler, D., Aha, D.W., & Albert,M. (1989). Instance-based prediction of real-valued attributes. Computational Intelligence, Vol 5, 51–57.

GSE documentation built on Dec. 28, 2022, 1:31 a.m.