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Level: Beginner
Recommended Use: Classification Models
Domain: Automobile

Car Evaluation Data Set

Predict acceptibility of a car


This intermediate level data set was derived from a decision-making model which was originally developed for research on multi-attribute decision making. Decision making involves selection between seemingly conflicting alternatives.

The data set has 1728 rows and 7 columns in which car attributes such as price and technology are described across 6 attributes such as "Buying Price", "Maintenance", and "Safety" etc. There are multiple alternatives under each of the 6 attributes. Car's acceptability, the seventh attribute, is the outcome variable.

This data set is recommended for learning and practicing your skills in classification modelling techniques. Feel free to explore the data set with multiple classification methods. The Following data dictionary gives more details on this data set:


Data Dictionary

Column Position Atrribute Name Definition Data Type Example % Null Ratios
1 buying Buying price of the car (v-high, high, med, low) Qualitative low, med, high 0
2 maint Price of the maintenance of car (v-high, high, med, low) Qualitative low, med, high 0
3 doors Number of doors (2, 3, 4, 5-more) Qualitative 2, 3, 4 0
4 persons Capacity in terms of persons to carry (2, 4, more) Qualitative 2, 4, more 0
5 lug_boot The size of luggage boot (small, med, big) Qualitative small, med, big 0
6 safety Estimated safety of the car (low, med, high) Qualitative low, med, high 0
7 class Car acceptability (unacc: unacceptible, acc: acceptible, good: good, v-good: very good) Qualitative unacc, acc, good 0

Acknowledgement

This data set has been sourced from the Machine Learning Repository of University of California, Irvine Car Evaluation Data Set (UC Irvine). The UCI page mentions following as the donor of the dataset:

  • Marko Bohanec (marko.bohanec '@' ijs.si)
  • Blaz Zupan (blaz.zupan '@' ijs.si)