Data
autos

autos

active ARFF Publicly available Visibility: public Uploaded 27-01-2023 by Young Lee
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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

26 features

class (target)numeric7 unique values
0 missing
normalized-lossesnumeric995250 unique values
0 missing
wheel-basenumeric966458 unique values
0 missing
lengthnumeric985867 unique values
0 missing
widthnumeric923762 unique values
0 missing
heightnumeric943102 unique values
0 missing
curb-weightnumeric999676 unique values
0 missing
engine-sizenumeric994182 unique values
0 missing
borenumeric621757 unique values
0 missing
strokenumeric608190 unique values
0 missing
compression-rationumeric675386 unique values
0 missing
horsepowernumeric994784 unique values
0 missing
peak-rpmnumeric999433 unique values
0 missing
city-mpgnumeric973545 unique values
0 missing
highway-mpgnumeric974625 unique values
0 missing
pricenumeric999968 unique values
0 missing
makenominal22 unique values
0 missing
fuel-typenominal2 unique values
0 missing
aspirationnominal2 unique values
0 missing
num-of-doorsnominal2 unique values
0 missing
body-stylenominal5 unique values
0 missing
drive-wheelsnominal3 unique values
0 missing
engine-locationnominal2 unique values
0 missing
engine-typenominal7 unique values
0 missing
num-of-cylindersnominal7 unique values
0 missing
fuel-systemnominal8 unique values
0 missing

19 properties

1000000
Number of instances (rows) of the dataset.
26
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
16
Number of numeric attributes.
10
Number of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
4
Number of binary attributes.
15.38
Percentage of binary attributes.
0
Percentage of instances having missing values.
1
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
61.54
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
38.46
Percentage of nominal attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
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