---
id: OPTICS
aliases:
  - OPTICS: Ordering Points To Identify Clustering Structure
tags: []
---

## OPTICS: Ordering Points To Identify Clustering Structure

![[CleanShot 2023-10-24 at 22.22.49@2x.png]] ![[CleanShot 2023-10-24 at
22.23.05@2x.png]]

## OPTICS (cont.)

- OPTICS does not explicitly produce a data set clustering.
- It outputs a cluster ordering.
  - It is a linear list of all objects under analysis and
  - Represents the density-based clustering structure of the data.
- Objects in a denser cluster are listed closer to each other in the cluster
  ordering
- Ordering is equivalent to density-based clustering obtained from a wide range
  of parameter settings.
- Thus OPTICS does not require the user to provide a specific density threshold.
- The cluster ordering can be used to extract basic clustering information
  (e.g., cluster centers, or arbitrary-shaped clusters), derive the intrinsic
  clustering structure, as well as provide a visualization of the clustering.
- It computes an ordering of all objects in a given database. And
- It stores the core-distance and a suitable reachability-distance for **each**
  object in the database.
- OPTICS maintains a list called **OrderSeeds** to help generate the output
  ordering.
- Objects in **OrderSeeds**
  - Are stored by the reachability-distance from their respective closet core
    objects,
  - That is, by the smallest reachability-distance of each object.