Data
cars

cars

active ARFF Publicly available Visibility: public Uploaded 22-12-2022 by Sebastian Fischer
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Data Description Data frame of the suggested retail prices (column *Price*) and various characteristics of each car. For this data set, a representative sample of over eight hundred 2005 GM cars were selected, then retail prices were calculated from the tables provided in the 2005 Central Edition of the Kelly Blue Book. Attribute Description All features describe different self-explanatory characteristics for the cars. 1. *Price* - target feature 2. *Mileage* 3. *Cylinder* 4. *Doors* 5. *Cruise* 6. *Sound* 7. *Leather* 8. *Buick* 9. *Cadillac* 10. *Chevy* 11. *Pontiac* 12. *Saab* 13. *Saturn* 14. *convertible* 15. *coupe* 16. *hatchback* 17. *sedan* 18. *wagon*

18 features

Price (target)numeric798 unique values
0 missing
Mileagenumeric791 unique values
0 missing
Cylindernumeric3 unique values
0 missing
Doorsnumeric2 unique values
0 missing
Cruisenumeric2 unique values
0 missing
Soundnumeric2 unique values
0 missing
Leathernumeric2 unique values
0 missing
Buicknumeric2 unique values
0 missing
Cadillacnumeric2 unique values
0 missing
Chevynumeric2 unique values
0 missing
Pontiacnumeric2 unique values
0 missing
Saabnumeric2 unique values
0 missing
Saturnnumeric2 unique values
0 missing
convertiblenumeric2 unique values
0 missing
coupenumeric2 unique values
0 missing
hatchbacknumeric2 unique values
0 missing
sedannumeric2 unique values
0 missing
wagonnumeric2 unique values
0 missing

19 properties

804
Number of instances (rows) of the dataset.
18
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.
18
Number of numeric attributes.
0
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.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
-3168.54
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.

2 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Price
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Price
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