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| KEEL-dataset - data set description |
This section describes main characteristics of the car data set and its attributes:
General information
| Car Evaluation data set | |||
|---|---|---|---|
| Type | Classification | Origin | Real world |
| Features | 6 | (Real / Integer / Nominal) | (0 / 0 / 6) |
| Instances | 1728 | Classes | 4 |
| Missing values? | No | ||
Attribute description
| Attribute | Domain |
|---|---|
| Buying | {vhigh,high,med,low} |
| Maint | {vhigh,high,med,low} |
| Doors | {2,3,4,5more} |
| Persons | {2,4,more} |
| Lug_boot | {small,med,big} |
| Safety | {low,med,high} |
| Acceptability | {unacc,acc,vgood,good} |
Additional information
Car Evaluation Database was derived from a simple hierarchical decision model. The model evaluates cars according to six input attributes: buying, maint, doors, persons, lug_boot, safety.
Because of known underlying concept structure, this database may be particularly useful for testing constructive induction and structure discovery methods.
In this section you can download some files related to the car data set:
- The complete data set already formatted in KEEL format can be downloaded from
here
. - A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here.
- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here.
- The header file associated to this data set can be downloaded from here
. - This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository . The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Car+Evaluation.
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