Anomaly Detection System
7.5/10Overall
7.5AI
No user ratings
Submitted Jul 18AI evaluated Jul 18
Prompt
Build anomaly detection system for data streams.
<data_stream>
- Type: {metrics/logs/transactions}
- Volume: {records per second}
- Dimensions: {number of features}
- Normal patterns: {describe typical behavior}
</data_stream>
<anomaly_types>
{point, contextual, collective anomalies}
</anomaly_types>
<business_requirements>
- False positive tolerance: {acceptable rate}
- Latency: {detection speed needs}
- Explainability: {why flagged}
</business_requirements>
Build system:
1. Method selection
- Statistical methods
- ML approaches (Isolation Forest, etc)
- Deep learning (Autoencoders)
- Ensemble strategies
2. Feature engineering
- Time-based features
- Statistical aggregates
- Seasonal adjustments
3. Threshold optimization
- Precision-recall trade-off
- Dynamic thresholds
- Anomaly scoring
4. Alerting design
- Alert prioritization
- Grouping strategies
- Notification rules
Include evaluation metrics.
AI Evaluation
How we evaluateClaude 3 Haiku
AI Evaluation
8.1/10
GPT-4 Mini
AI Evaluation
7.0/10
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