The predicting of fare amount (inclusive of tolls) for a taxi ride, given the pickup and dropoff locations,the pickup date time and many other attributes given below.
The description of all the attributes is given below.
The target variable is “fare_amount “
Understand the data and do necessary data exploration and try creating new features and build a machine learning model to predict the fare amount.
Variable Description
TID Unique ID
Vendor_ID Technology service vendor associated with cab company
New_User If a new user is taking the ride
toll_price toll tax amount
tip_amount tip given to driver (if any)
tax applicable tax
pickup_timestamp time at which the ride started
dropoff_timestamp time at which ride ended
passenger_count number of passenger during the ride
pickup_longitude pickup location longitude data
pickup_latitude pickup location latitude data
rate_category category assigned to different rates at which a customer is charged
store_and_fwd if driver stored the data offline and later forwarded
dropoff_longitude drop off longitude data
dropoff_latitude drop off latitude data
payment_type payment mode used by the customer (CRD = Credit Card, CSH - Cash, DIS - dispute, NOC - No Charge, UNK - Unknown)
surcharge surchage applicable on the trip
fare_amount trip fare (to be predicted)