Challenge has Ended

Cab Fare Prediction AI Challenge

The aim of the challenge is to predict the cab fare using the given dataset.

Difficulty

Community
Challenge
Bounty for Rank 1
₹5,000.00
Certificate
Ended
342 Participants
9,225 Views
Organized By Dockship

Welcome to Cab Fare Prediction AI Challenge!

The aim of the challenge is to predict the cab fare using the given dataset. The dataset consists of 3 CSV files:

  1. TRAIN.csv
  2. TEST.csv
  3. sample_submission.csv

TRAIN.csv consists of 9 attributes:

  • index
  • time_stamp - epoch time (in seconds) when the cab was booked
  • cab_provider - company (Uber/Lyft)
  • source - the starting point of the cab ride
  • destination - the destination of the cab ride
  • distance - the distance between source and destination
  • surge_multiplier - multiplier by which price increased
  • cab_type - the type of cab (Uber Pool, Uber XL, etc. )
  • fare - cab fare in USD (Target Attribute)

This data should be used to train the model, no additional data is allowed to be used for the training process.

TEST.csv consists of the testing data required for prediction and consists of 8 attributes:

  • index
  • time_stamp - epoch time (in seconds) when the cab was booked
  • cab_provider - company (Uber/Lyft)
  • source - the starting point of the cab ride
  • destination - the destination of the cab ride
  • distance - the distance between source and destination
  • surge_multiplier - multiplier by which price increased
  • cab_type - the type of cab (Uber Pool, Uber XL, etc. )

A "sample_submission".csv is also provided for ease of the participants. To know the exact submission format, please check out "Submission Guidelines".

The score is displayed in reverse order of Root Mean Square Error (RMSE). "TRAIN.csv" file contains the data required for training.

The output of the model should be "output.csv" containing the following columns in this exact order for predictions on TEST.csv:

  • index (Row index of TEST.csv data)
  • fare (Target Attribute)

A "sample_submission.csv" is also given for reference which already contains the correct format required for submission.

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How to make a submission?

  1. Click on "My Submission"
  2. On the next page, click on "+ New Submission"
  3. Upload your CSV in the next page and click on "Submit for Review"

Please note:

  1. You must submit your CSV file by uploading the CSV in the "My Submissions" section of this challenge.
  2. Your submission will be auto graded and you will be able to see your results instantly.
  3. If there is any error in the submission, your final score will be marked as 0.

Judgment

  1. Root Mean Squared Error (RMSE) will be used for evaluation
  2. If the scores are tied, the person reaching the score FIRST will get the better rank.

Rules

  1. We are using an automatic anti-cheat system. Our system flags submission which has low trust scores. Manually modifying your submission CSV (via comparison of any form etc.), using image comparison techniques (pixel matching, file size matching, etc.), in any form, can lead to your disqualification without any notice.
  2. The participants must use only the provided dataset for training.
  3. The submission should be in a proper format as described by "Submission Guidelines".
  4. Late submission will not be accepted beyond the provided deadline (Indian Standard Time).

NOTE: We may request the code files if there is any discrepancy in your score. Your score will be marked invalid or you can be disqualified if the request for code is not fulfilled by you.

Rewards:

  1. The winner will receive a cash prize of 5000 INR.
  2. The participants with a successful submission will get a certificate of participation.
  3. Top 3 participants will receive a permanent place in Dockship's "Hall of Fame".

Top 5 Participants will also earn Dockship gems:

  • Rank 1: 250 💎
  • Rank 2: 150 💎
  • Rank 3: 100 💎
  • Rank 4: 50 💎
  • Rank 5: 50 💎
How do I apply for this Challenge?
How do I download the dataset?
Can I make multiple submissions?
Where will the results be declared?
Can we apply as a team?
I've other queries, where can I get support?
Challenge Announced
31-Mar-2021, 10:19 am IST
04-Apr-2021, 12:00 pm IST
Challenge Started
Challenge Ended
04-Jun-2021, 10:00 pm IST