Data Anomaly Detection

Input Data (JSON Array)

Anomaly Detection Configuration

Example Input

[
  {
    "timestamp": "2023-01-01",
    "temperature": 20.5,
    "humidity": 45
  },
  {
    "timestamp": "2023-01-02",
    "temperature": 21.2,
    "humidity": 47
  },
  {
    "timestamp": "2023-01-03",
    "temperature": 35.8,
    "humidity": 42
  }
]

Detection Methods:

  • Z-Score: Identifies values beyond a number of standard deviations from the mean
  • IQR: Uses quartiles to identify values far from the central range
  • Isolation Forest: Machine learning approach that isolates anomalies
  • Moving Average: Compares values to local averages within a sliding window