Welcome to GitHub Repository for Kaggle home site quote conversion.
Description
Before asking someone on a date or skydiving, it's important to know your likelihood of success. The same goes for quoting home insurance prices to a potential customer. Homesite, a leading provider of homeowners insurance, does not currently have a dynamic conversion rate model that can give them confidence a quoted price will lead to a purchase.
Data
This dataset represents the activity of a large number of customers who are interested in buying policies from Homesite. Each QuoteNumber corresponds to a potential customer and the QuoteConversion_Flag indicates whether the customer purchased a policy.
The provided features are anonymized and provide a rich representation of the prospective customer and policy. They include specific coverage information, sales information, personal information, property information, and geographic information. Your task is to predict QuoteConversion_Flag for each QuoteNumber in the test set.
File descriptions
- train.csv - the training set, contains QuoteConversion_Flag
- test.csv - the test set, does not contain QuoteConversion_Flag
- sample_submission.csv - a sample submission file in the correct format
Evaluation
Submissions are evaluated on area under the ROC curve between the predicted probability and the observed target.
Using an anonymized database of information on customer and sales activity, including property and coverage information, Homesite is challenging you to predict which customers will purchase a given quote. Accurately predicting conversion would help Homesite better understand the impact of proposed pricing changes and maintain an ideal portfolio of customer segments.
Authors and Contributors
The autor for this proyect:
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