Statements (29)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:advantage |
finds clusters of varying density
|
| gptkbp:field |
gptkb:machine_learning
data mining |
| gptkbp:fullName |
gptkb:Ordering_Points_To_Identify_the_Clustering_Structure
|
| https://www.w3.org/2000/01/rdf-schema#label |
OPTICS
|
| gptkbp:input |
gptkb:Metric
spatial data epsilon parameter minPts parameter |
| gptkbp:introduced |
gptkb:Hans-Peter_Kriegel
gptkb:Jörg_Sander gptkb:Markus_M._Breunig gptkb:Mihael_Ankerst |
| gptkbp:introducedIn |
1999
|
| gptkbp:openSource |
gptkb:ELKI
gptkb:scikit-learn |
| gptkbp:output |
cluster ordering
reachability plot |
| gptkbp:publishedIn |
gptkb:ACM_SIGMOD_International_Conference_on_Management_of_Data
|
| gptkbp:purpose |
identify density-based clusters in spatial data
|
| gptkbp:relatedTo |
gptkb:DBSCAN
|
| gptkbp:supportsAlgorithm |
gptkb:HDBSCAN
gptkb:DBSCAN |
| gptkbp:usedIn |
data analysis
anomaly detection spatial clustering |
| gptkbp:bfsParent |
gptkb:DBSCAN
|
| gptkbp:bfsLayer |
6
|