Find unusual records in your data and compare methods.
What it does
Identifies anomalous data records and compares detection methods to guide production deployment.
When to use it
Use for detecting financial fraud, system failures, security breaches, manufacturing defects, unusual healthcare patterns, abnormal sensor readings, or customer behavior outliers.
How to use it
Give it data to analyze; it returns anomalous records, score visualizations, method comparisons, and recommendations for thresholds and production deployment.
What you provide
- Your files
What you need · 7
The implementation requires Python; no version is specified.
The implementation imports pandas for data tables and rolling statistics.
The implementation imports numpy for numerical operations and sample data generation.
The implementation imports matplotlib.pyplot to produce visualizations.
Access · 0
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