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---
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.
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