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This data set used in the CoIL 2000 Challenge contains information on customers of an insurance company. The data consists of 86 variables and includes product usage data and socio-demographic data
DETAILED DATA DESCRIPTION
THE INSURANCE COMPANY (T..
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Context
Insurance companies that sell life, health, and property and casualty insurance are using machine learning (ML) to drive improvements in customer service, fraud detection, and operational efficiency. The data provided by an Insurance company..
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Context
The insurance.csv dataset contains 1338 observations (rows) and 7 features (columns). The dataset contains 4 numerical features (age, bmi, children and expenses) and 3 nominal features (***, smoker and region) that were converted into factor..
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Introduction
Here you find a very simple, beginner-friendly data set. No sparse matrices, no fancy tools needed to understand what's going on. Just a couple of rows and columns. Super simple stuff.As explained below, this data set is used for a comp..
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This data set used in the CoIL 2000 Challenge contains information on customers of an insurance company. The data consists of 86 variables and includes product usage data and socio-demographic data derived from zip area codes. The data was collected ..
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In this dataset, you are provided over a hundred variables describing attributes of life insurance applicants. The task is to predict the "Response" variable for each Id in the test set. "Response" is an ordinal measure of risk that has 8 levels.
Fi..
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A third-party travel insurance servicing company that is based in Singapore.
The attributes:
Target: Claim Status (Claim.Status)
Name of agency (Agency)
Type of travel insurance agencies (Agency.Type)
Distribution channel of travel insurance a..
