Ablation Study Results on NYC-Taxi and CH-Bike Drop-off Prediction

Ablation study results for drop-off prediction models applied to New York City taxi and CH-Bike data. The dataset was authored by Sadia Tabassum and last updated on May 19, 2026. It is a small 5.5 KB file available in XLS format under a CC-BY-4.0 license.

Use Cases

• Compare model performance variations based on the ablation study results described.
• Analyze feature contributions to drop-off prediction accuracy for taxi and bike-sharing systems.
• Benchmark predictive modeling approaches for urban transportation datasets like NYC-Taxi and CH-Bike.

Strengths

• Small 5.5 KB size enables quick download and inspection.
• Explicitly licensed under the permissive CC-BY-4.0 license.
• Specific focus on ablation study results for two distinct transportation datasets.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Sadia Tabassum via figshare

Collection Method

Likely contains results from computational experiments or model evaluations.

Freshness

Last updated 2026-05-19 17:35:32; freshness should be verified.

Geography

New York City (NYC-Taxi) and an unspecified location for CH-Bike.