Statements (23)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:advantage |
does not require number of clusters as input
finds clusters of varying shapes and sizes |
| gptkbp:author |
gptkb:Leland_McInnes
gptkb:John_Healy gptkb:Steve_Astels |
| gptkbp:availableOn |
scikit-learn compatible API
|
| gptkbp:basedOn |
gptkb:DBSCAN
|
| gptkbp:category |
density-based clustering
hierarchical clustering |
| gptkbp:citation |
McInnes, L., Healy, J., & Astels, S. (2017). hdbscan: Hierarchical density based clustering. The Journal of Open Source Software, 2(11), 205.
|
| gptkbp:fullName |
gptkb:Hierarchical_Density-Based_Spatial_Clustering_of_Applications_with_Noise
|
| gptkbp:handles |
clusters of varying densities
noise in data |
| https://www.w3.org/2000/01/rdf-schema#label |
HDBSCAN
|
| gptkbp:implementedIn |
gptkb:Python
|
| gptkbp:introducedIn |
2015
|
| gptkbp:openSource |
true
|
| gptkbp:repository |
https://github.com/scikit-learn-contrib/hdbscan
|
| gptkbp:usedFor |
data clustering
unsupervised machine learning |
| gptkbp:bfsParent |
gptkb:DBSCAN
|
| gptkbp:bfsLayer |
6
|