Mindmap
Clustering Algorithms
Inhalt der Mindmap
Clustering Algorithms
k-Means
- Strengths
- Weaknesses
Hierarchical Agglomerative Clustering
DBSCAN
- Strengths
- Noise resistant
- Able to handle arbitrary shapes and sizes
- Weaknesses
- Trouble w/ clusters of widely varying density
- expensive when computation of nearest neighbors requires computing all pairwise proximities
- Strengths
Informationen
- Beschreibung
- Mindmap am Clustering Algorithms, erstellt von Ian Kinskey am 03/11/2017.
- Erstellt von
- Ian Kinskey
- Aufrufe
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