Data Science Dojo
Copyright (c) 2016 - 2019
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**Level:** Beginner
**Recommended Use:** Classification Models
**Domain:** Automobile
## Car Evaluation Data Set
### Predict acceptibility of a car
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This *beginner* 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:
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### 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 |
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### Acknowledgement
This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Car Evaluation Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Car+Evaluation). The UCI page mentions following as the donor of the dataset:
+ Marko Bohanec (marko.bohanec '@' ijs.si)
+ Blaz Zupan (blaz.zupan '@' ijs.si)