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Learn ML Insurance Prediction AI Challenge

The aim of this challenge is to predict whether the customer will be interested in buying insurance.

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Welcome to Learn ML Insurance Prediction AI Challenge!

The aim of this challenge is to predict whether the customer will be interested in purchasing additional insurance for vehicles. Building systems for customer segmentation which ease in targeting potential customers for selling products or services is a huge requirement in companies these days. The use may be of insurance, user subscription and many more.

The dataset consists of the following attributes:

  • id (Unique ID for the customer)
  • Gender
  • Age
  • Driving License (0: Not present, 1: have one)
  • Region_Code
  • Previously_Insured (1: already has insurance, 0: doesn't have)
  • Vehicle_Age
  • Vehicle_Damage (1: customer got vehicle damage in past, 0: no past history of damage)
  • Annual_Premium (Amount to be paid annually)
  • PolicySalesChannel
  • Vintage (Number of days customer has been in the company)
  • Response ('Target Column' ) (1: Customer is interested, 0: not interested)

as part of the "TRAIN.csv" file provided for training. No additional data may be used for training.

The test set consists of "TEST.csv" for all the same attributes as "TRAIN.csv" except for the target column. There is an additional "sample_submission.csv" provided to give an example submission. A screenshot is also attached in Submission Guidelines.


Please refer to the Submission Guidelines for the final format of the submission.

The final submission must include:

output.csv (single file having results for "TEST.csv").

The first row should correspond to the column names "id" (as provided in TEST.csv) and "Response" (prediction results).

Sample Output:


...

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 or a warning prompt of “Invalid Score” will be displayed.

Judgement

  1. F1 Accuracy Score
  2. If the scores are tied, the person reaching the score FIRST will get the better rank.

Rules

  1. We are using automatic anti-cheat system. Our system flags submission which have 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 provided deadline (Indian Standard Time).

NOTE: We may request for 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.


  1. Top 3 participants will receive T-shirts from LearnML.
  2. Top 3 participants will be added to Dockship's Hall of Fame page.
  3. The participants with a successful submission will get a certificate of participation.
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?
More information about the dataset.
Challenge Announced
Nov 24, 2020, 12:22 PM IST
Jan 15, 2021, 6:00 PM IST
Challenge Started
Challenge Ends
Feb 08, 2021, 11:55 PM IST