Dark Mode
Car Evaluation Criteria Dataset
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
The Car Acceptability Classification Dataset enables the classification of a car's overall acceptability based on several key criteria. This dataset was derived from a straightforward hierarchical decision model, initially created to demonstrate the DEX expert system in 1990. It systematically evaluates cars by applying a specific concept structure, making it suitable for modelling car evaluation processes.
Columns
- Buying_Price: A categorical variable indicating the purchasing cost of the car. Possible values include: vhigh, high, med, low.
- Maintenance_Price: A categorical variable representing the cost associated with maintaining the car. Possible values include: vhigh, high, med, low.
- No_of_Doors: A categorical variable detailing the number of doors on the car. Possible values include: 2, 3, 4, 5more.
- Person_Capacity: A categorical variable specifying the maximum passenger capacity of the car. Possible values include: 2, 4, more.
- Size_of_Luggage: A categorical variable describing the storage capacity of the car's luggage boot. Possible values include: small, med, big.
- Safety: A categorical variable assessing the safety rating of the car. Possible values include: low, med, high.
- Car_Acceptability: The target categorical variable, which indicates the determined acceptability level of the car. Possible values include: unacc, acc, good, vgood.
Distribution
The dataset is provided as a CSV file, specifically named 'car.csv', and has a file size of 51.97 kB. It contains 7 distinct columns, all of which are represented by categorical data. There are 1728 valid entries across all records within the dataset.
- Buying_Price: Features 4 unique values, with 'vhigh' being the most frequently occurring at 25% of entries.
- Maintenance_Price: Also features 4 unique values, with 'vhigh' being the most frequently occurring at 25% of entries.
- No_of_Doors: Presents 4 unique values, with '2' being the most frequently occurring at 25% of entries.
- Person_Capacity: Has 3 unique values, with '2' being the most frequently occurring at 33% of entries.
- Size_of_Luggage: Offers 3 unique values, with 'small' being the most frequently occurring at 33% of entries.
- Safety: Provides 3 unique values, with 'low' being the most frequently occurring at 33% of entries.
- Car_Acceptability: Contains 4 unique values, with 'unacc' being significantly the most frequently occurring at 70% of entries.
Usage
This dataset is ideally suited for a variety of applications, including:
- Developing and testing machine learning models for classification tasks.
- Creating data visualisation projects to explore relationships between car features and acceptability.
- Serving as an approachable dataset for beginners in data science and analytics.
- Demonstrating and building expert systems or decision support tools.
Coverage
The available sources do not specify any particular geographic, time range, or demographic scope for this dataset. The underlying decision model from which the dataset was derived was initially developed in 1990.
License
CC BY-NC-SA 4.0
Who Can Use It
- Data Scientists and Machine Learning Engineers: For training and evaluating classification algorithms focused on categorical data.
- Students and Academics: As an accessible and well-defined dataset for educational purposes in data analysis, classification, and expert systems.
- Researchers: Investigating car evaluation criteria, decision models, or the application of machine learning in consumer choice.
- Developers: Interested in building predictive models that assess car acceptability based on given attributes.
Dataset Name Suggestions
- Car Evaluation Criteria Dataset
- Vehicle Acceptability Modelling Data
- Automobile Classification Attributes
- Car Decision Support Dataset
Attributes
Original Data Source: Car Evaluation Criteria Dataset
QUALITY