Often related to severity or churn , such as "Crash Severity" or "Customer Churn".
Demographic info, technical logs, or incident-based data (e.g., timestamps, location coordinates, event types).
Applying Logistic Regression or Decision Trees to predict outcomes based on the features. Siu0207_2019.zip
💡 If you are using this for a course assignment, ensure you check for any "Data Dictionary" files inside the zip; these define every column (feature) and its measurement scale. To help you build the feature or model you need:
Do you need a to extract and load this specific zip into a dataframe? Often related to severity or churn , such
Usually contains a single large CSV or Excel file intended for processing in Python (Pandas) or SAS . Common Analysis Workflow
Creating confusion matrices and ROC curves to evaluate model performance. 💡 If you are using this for a
While the exact columns depend on the specific version, students typically analyze these features for classification or regression tasks: