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TAXI NYC ’19, home

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Estimate a trip

How long will it take?

The regression from the 2021 notebook, running in your browser: 579 features, the original coefficients from fold 1 of its 10-fold cross-validation. Across the folds it explained 36.7% of the variance with a typical error of 9.2 minutes, so each prediction now comes with a split-conformal prediction interval that held its stated coverage on 7.5 million held-out 2019 trips.

Manhattan–JFK rides are billed at the flat fare, rate code 2.

Vendor
Vendor
Store-and-forward
Store and forward flag

Y when the meter stored the trip offline before sending it.

That day, Manhattan

Wednesday · 55.0 °F · rain 0.54 in · snow 0.0 in · 265 events · 46 collisions

2021 model predicts

43.0min

Midtown Center → JFK Airport, Wednesday at 5 pm

90% prediction interval: 32.0 to 68.6 min

Interval level
04080 min

Split-conformal, from 687,938 held-out 2019 trips picked up in Manhattan with a similar prediction (bin 10 of 10). On 688,079 other Manhattan trips in the same bin, 90.0% fell inside (95% CI 89.8% to 90.2%, resampling whole days). Solid line: the prediction. Dashed blue line: the observed median at this hour. How the intervals are built

2026 refit, same features
42.7 min
Observed median, 5 pm
…
Observed median, any hour
…
Straight-line distance
12.6 mi

Why that number

A linear model is a sum. The 2021 model starts from an intercept of 22.35 minutes and adds one coefficient per active feature. Bars show what each part of your trip adds or removes.

  • Weather, events, collisions+1.62
  • Weekday0.00
  • Hour+0.98
  • Rate code+9.29
  • Passengers0.00
  • Pickup zone0.00
  • Vendor0.00
  • Drop-off zone+8.78
  • Store-and-forward flag0.00
  • Intercept + all terms22.35 with 4 non-zero terms43.02

Red adds minutes, blue removes them. Zones, hours and weekdays are relative to the categories the penalty set to zero. Coefficients: coursework/10-folds-linear-regression.csv, fold 1.

Map: click a zone to set the pickup or drop-off

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