Use case on the nyc_taxi_gree_dec2016 dataset

Dataset nyc-taxi-green-dec-2016

Machine Learning Task: Regression

This is a Trip Record Data database. It is provided by the New York City Taxi and Limousine Commission (TLC). The dataset included TLC trips of the green line in December 2016.

Available at OpenML:

Category: Automotive

# Rows: 581,835 # Columns: 18

Target: tip_amount


Numeric: passenger_count, tolls_amount, total_amount, lpep_pickup_datetime_day, lpep_pickup_datetime_hour, lpep_pickup_datetime_minute, lpep_dropoff_datetime_day, lpep_dropoff_datetime_hour, lpep_dropoff_datetime_minute

Nominal: VendorID, store_and_fwd_flag, RatecodeID, PULocationID, DOLocationID, extra, mta_tax, improvement_surcharge, trip_type

Machine Learning Use Case Automotive

Root Mean Square Error (RMSE)

Nyc_Taxi_Gree_Dec2016 Rmse

Mean Absolute Error (MAE)

Nyc_Taxi_Gree_Dec2016 Mae

Coefficient of Determination (R2)

Nyc_Taxi_Gree_Dec2016 R2

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