﻿---
title: Anomaly detection algorithms
description: The anomaly detection machine learning features use a combination of advanced mathematical techniques such as clustering, various types of time series...
url: https://docs-v3-preview.elastic.dev/elastic/docs-content/pull/3897/explore-analyze/machine-learning/anomaly-detection/ml-ad-algorithms
products:
  - Machine Learning
---

# Anomaly detection algorithms
The anomaly detection machine learning features use a combination of advanced mathematical techniques such as clustering, various types of time series decomposition, Bayesian distribution modeling, and correlation analysis. These analytics provide sophisticated real-time automated anomaly detection for time series data.
The machine learning analytics statistically model the time-based characteristics of your data by observing historical behavior and adapting to new data. The model represents a baseline of normal behavior and can therefore be used to determine how anomalous new events are.
Anomaly detection results are written for each [bucket span](/elastic/docs-content/pull/3897/explore-analyze/machine-learning/anomaly-detection/ml-ad-run-jobs#ml-ad-bucket-span). These results include scores that are aggregated in order to reduce noise and normalized in order to rank the most mathematically significant anomalies.