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Car Evaluation Dataset

This repository contains the Car Evaluation dataset, which was donated on 5/31/1997. The dataset is derived from a simple hierarchical decision model and may be useful for testing constructive induction and structure discovery methods.

Dataset Characteristics

  • Type: Multivariate
  • Subject Area: Other
  • Associated Tasks: Classification
  • Feature Type: Categorical
  • Number of Instances: 1728
  • Number of Features: 6

Dataset Information

The 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 in lowercase. Besides the target concept (CAR), the model includes three intermediate concepts: PRICE, TECH, and COMFORT. Each concept is related to its lower-level descendants by a set of examples.

The Car Evaluation Database contains examples with the structural information removed, directly relating CAR to the six input attributes: buying, maint, doors, persons, lug_boot, and safety.

Due to its known underlying concept structure, this database may be particularly useful for testing constructive induction and structure discovery methods.

  • Missing Values: No

References

  • M. Bohanec, V. Rajkovic: Expert system for decision making. Sistemica 1(1), pp. 145-157, 1990.
  • For more information on the original model and example sets, visit: DEX Car Model.

Usage

You can find the Car_Evaluation.ipynb notebook in this repository, which contains the analysis and use of the Car Evaluation dataset.

License

This dataset is available for public use. Please refer to the original publication for citation.

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