Car Evaluation Database was derived from a simple hierarchical decision model originally developed for the demonstration of DEX.

car_eval

Format

A data frame with 1728 observations on the following 7 variables.

  1. buying

  2. maint

  3. doors

  4. persons

  5. lug_boot

  6. safety

  7. class

Source

Creator: Marko Bohanec

Donors:

  1. Marko Bohanec (marko.bohanec '@' ijs.si)

  2. Blaz Zupan (blaz.zupan '@' ijs.si)

Details

Derived from simple hierarchical decision model, this database may be useful for testing constructive induction and structure discovery methods.

Car Evaluation Database was derived from a simple hierarchical decision model originally developed for the demonstration of DEX. The model evaluates cars according to the following concept structure:

  • CAR: car acceptability

  • PRICE: overall price (buying buying price, maint price of the maintenance)

  • TECH: technical characteristics

  • COMFORT: comfort (doors number of doors, persons capacity in terms of persons to carry, lug_boot the size of luggage boot, safety estimated safety of the car)

Input attributes are printed in lowercase. Besides the target concept (CAR), the model includes three intermediate concepts: PRICE, TECH, COMFORT. Every concept is in the original model related to its lower level descendants by a set of examples.

The Car Evaluation Database contains examples with the structural information removed, i.e., directly relates CAR to the 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.

References

M. Bohanec, V. Rajkovic: Expert system for decision making. Sistemica 1(1), pp. 145-157, 1990.)

M. Bohanec and V. Rajkovic: Knowledge acquisition and explanation for multi-attribute decision making. In 8th Intl Workshop on Expert Systems and their Applications, Avignon, France. pages 59-78, 1988.

B. Zupan, M. Bohanec, I. Bratko, J. Demsar: Machine learning by function decomposition. ICML-97, Nashville, TN. 1997

https://archive.ics.uci.edu/ml/machine-learning-databases/car/

https://archive.ics.uci.edu/ml/datasets/Car+Evaluation