Motorcycle Accident Severity Prediction Data for Pakistan

Synthetic data simulating motorcycle accident severity in Pakistan. The dataset is designed for classification tasks, though its specific size and creation date are unknown.

Use Cases

• Predict accident_severity using synthetic features like road_condition and weather.
• Classify accident outcomes based on simulated rider attributes such as age or helmet_use.
• Train a model to identify high-risk scenarios from synthetic variables like time_of_day and vehicle_type.
• Benchmark classification algorithms on a synthetic tabular dataset with a severity_label target.

Strengths

• Synthetic nature allows for controlled experimentation without privacy concerns.
• Designed specifically for multiclass classification tasks.

Limitations

• Data is synthetic and may not reflect real-world accident patterns or distributions.
• Unknown row count prevents assessment of dataset scale for model training.

Provenance

Source

Kaggle

Collection Method

Synthetically generated.

Geography

Pakistan