Data Science Dojo
Copyright (c) 2016 - 2019 --- **Level:** Beginner
**Recommended Use:** Classification Models
**Domain:** Automobile
## Car Evaluation Data Set ### Predict acceptibility of a car --- ![](1190.jpg) --- 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)](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)