Taxi Fare Prediction Data for Machine Learning

A dataset for predicting taxi fares, sourced from Kaggle. The specific number of records, features, and geographic scope are not detailed in the provided metadata. Further details on the data's origin, size, and structure require verification after download.

Use Cases

• Train a regression model to predict trip cost from features like distance and time (inferred from domain, verify after download)
• Benchmark machine learning algorithms on a structured prediction task (inferred from domain, verify after download)
• Analyze factors influencing urban transportation pricing (inferred from domain, verify after download)

Strengths

• Published on Kaggle, a platform with an active community for data science.
• The title clearly indicates a supervised machine learning task (prediction).

Limitations

• Metadata is minimal; actual content requires verification after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file format, and license are unknown, which may limit suitability assessment.

Provenance

Source

Kaggle