anomaly-detector

name	anomaly-detector
description	Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.
allowed-tools	Read Write Edit Bash

Anomaly Detector

Audience: Data engineers and analysts detecting outliers in datasets.

Goal: Provide production-ready anomaly detection functions for various data types.

Scripts

Execute detection functions from scripts/anomaly_detection.py:

from scripts.anomaly_detection import (
    detect_anomalies_zscore,
    detect_anomalies_iqr,
    detect_anomalies_modified_zscore,
    detect_anomalies_isolation_forest,
    detect_anomalies_lof,
    detect_anomalies_rolling,
    detect_anomalies_stl,
    detect_anomalies_ensemble
)

Method Selection

Method	Best For	Limitations
Z-Score	Normal distributions	Sensitive to outliers
IQR	Skewed distributions	Less sensitive overall
Modified Z-Score	Robust detection	Slower computation
Isolation Forest	High-dimensional data	Requires tuning
LOF	Local density anomalies	Computationally expensive
Rolling	Time-series with trends