nmandery/extended-isolation-forest

Rust port of the extended isolation forest algorithm for anomaly detection

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/ 100
Emerging

This tool helps identify unusual or unexpected data points within a dataset, like pinpointing an anomalous jump in movement recordings or a sensor reading that falls outside normal operating parameters. You provide it with your numerical data, and it outputs a score indicating how likely each data point is an anomaly. This is useful for data analysts, quality control engineers, or anyone monitoring system performance or sensor data.

20 stars and 9,199 monthly downloads. No commits in the last 6 months.

Use this if you need to automatically detect rare or suspicious observations in your numerical data without prior labeling of anomalies.

Not ideal if your data is primarily categorical or textual, or if you already have labeled examples of what constitutes an anomaly.

anomaly-detection quality-control sensor-monitoring fraud-detection time-series-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 15 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

20

Forks

6

Language

Rust

License

MIT

Last pushed

Apr 26, 2023

Monthly downloads

9,199

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/nmandery/extended-isolation-forest"

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