anomaly-detector

What problem does it solve?

Detect unusual patterns, outliers, and anomalies in data using statistical methods, machine learning, and deep learning. This helps reduce fraud, security incidents, and operational anomalies by surfacing unusual behavior early and automating anomaly scoring within SpecWeave increments.

Core Features & Use Cases

• Unsupervised & Semi-supervised anomaly detection across time-series and high-dimensional data
• Multiple detectors: Isolation Forest, One-Class SVM, Autoencoders, Statistical methods (Z-score, IQR), LOF
• Increment integration: Emit anomaly scores and contributing factors into SpecWeave increments for quick remediation
• Use cases include fraud detection, system health monitoring, security/intrusion detection, and quality control.

Quick Start

Run the anomaly-detector for increment 0042 to scan your data and output anomaly scores.