Difference between revisions of "Hierarchical Cluster Analysis (HCA)"
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* [[Capabilities]] | * [[Capabilities]] | ||
* [[...find outliers]] | * [[...find outliers]] | ||
| + | * [[Clustering]] | ||
# Identify clusters (items) with closest distance | # Identify clusters (items) with closest distance | ||
Revision as of 19:43, 22 April 2019
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- Hierarchical Clustering; Agglomerative (HAC) & Divisive (HDC)
- Hierarchical Temporal Memory (HTM)
- Capabilities
- ...find outliers
- Clustering
- Identify clusters (items) with closest distance
- Join them to new clusters
- Compute distance between clusters (items)
- Return to step 1
The HCPC (Hierarchical Clustering on Principal Components) approach allows us to combine the three standard methods used in multivariate data analyses (Husson, Josse, and J. 2010):
