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diff --git a/SI/Resource/Fundamentals of Data Mining/Content/OPTICS.md b/SI/Resource/Fundamentals of Data Mining/Content/OPTICS.md new file mode 100644 index 0000000..3578883 --- /dev/null +++ b/SI/Resource/Fundamentals of Data Mining/Content/OPTICS.md @@ -0,0 +1,35 @@ +--- +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. |