autos
OpenML dataset with id 45080
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22112038/autos.arff
Upload date: 27 January 2023
Dataset Characteristics
Number of classes: 0
Number of features: 26 (numeric: 16, symbolic: 10 and in total binary: 4 )
Number of instances: 1,000,000
Number of instances with missing values: 0
Number of missing values: 0
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.Source: https://www.kaggle.com/datasets/toramky/automobile-dataset
This page was built for dataset: autos
