Insurance Risk Prediction with Demographic Factors

Coil2000 is a tabular dataset used for insurance risk modeling and marketing analysis. It contains demographic and insurance-related features, as indicated by its platform tags. The dataset was contributed to the OpenML repository for machine learning benchmarking.

Use Cases

• Predicting customer insurance risk based on demographic features like age and income.
• Analyzing the correlation between demographic columns and policy purchase decisions for marketing.
• Training binary classifiers to identify high-risk customer segments from tabular attributes.
• Benchmarking feature selection methods on a dataset with mixed demographic and risk variables.

Strengths

• Dataset is hosted on OpenML, a curated platform for machine learning data.
• Includes labeled fields for supervised learning tasks like classification.

Limitations

• Exact row count, column list, and sample size are unknown, limiting reproducibility.
• The absence of a detailed description obscures data collection methodology and potential biases.
• Temporal coverage and geographic scope are unspecified, reducing context for analysis.

Provenance

Source

OpenML repository.