There are 11 columns in the dataset. Some of them are mentioned below:

Duration: Travel duration
Destination: Travel destination
Agency: Agency Name
Commission: Commission on the insurance
Age: Age of the insurance buyer
Gender: Gender of the insurance buyer
Agency Type: What is the agency type?
Distribution Channel: offline/online
Product Name: Name of the insurance plan
Net Sales: Net sales
Claim: If the insurance is claimed or not (the target variable), 0 = not claimed, 1 = claimed

To load the training data in your jupyter notebook, use the below command:

import pandas as pd

insurance_data = pd.read_csv("https://raw.githubusercontent.com/dphi-official/Datasets/master/travel_insurance/Training_set_label.csv" )

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below.

prediction

0

0

0

1

0

1

.

.

Etc.

Note that the header name should be prediction else it will throw an evaluation error. A sample submission file can be found here

Load the test data (name it as test_data). You can load the data using the below command.

test_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/travel_insurance/Testing_set_label.csv')

Here the target column is deliberately not there as you need to predict it

Travel Insurance Claim Prediction