Hyndai Car Dataset

Published: 16 April 2024| Version 1 | DOI: 10.17632/bkym8ksp3h.1
ankita gupta,


Description: The dataset contains information on 100 cars, with each row representing a single car. The data was generated to simulate various characteristics and maintenance aspects of cars, including engine temperature, brake pad thickness, tire pressure, maintenance type, and anomaly indication variables. Variables: Engine Temperature (Continuous): Represents the temperature of the engine in degrees Celsius. Values range from approximately 70 to 100 degrees Celsius. Brake Pad Thickness (Continuous): Indicates the thickness of brake pads in millimeters. Values range from approximately 5 to 15 millimeters. Tire Pressure (Continuous): Represents the pressure of tires in pounds per square inch (PSI). Values range from approximately 28 to 36 PSI. Maintenance Type (Categorical): Indicates the type of maintenance performed on the car. Categories include "routine maintenance," "component replacement," and "repair." Anomaly Indication (Binary): Indicates the presence or absence of anomalies detected in sensor readings. Binary variable where 0 represents the absence of anomalies, and 1 represents the presence of anomalies. Usage: This dataset can be used for various analytical purposes, including exploratory data analysis, predictive modeling, and anomaly detection. Researchers and analysts can analyze the relationships between different variables to identify patterns and insights related to car maintenance and performance. Machine learning models can be trained using this data to predict maintenance requirements, detect anomalies in sensor readings, or optimize maintenance schedules for improved efficiency and cost-effectiveness.

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