Recursive Partitional Clustering Algorithm: Difference between revisions

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** A [[k-Means Clustering Algorithm]], such as [[bisecting k-means]].
** A [[k-Means Clustering Algorithm]], such as [[bisecting k-means]].
** A [[k-Medoid Clustering Algorithm]].
** A [[k-Medoid Clustering Algorithm]].
** ...
**
* <B>Counter-Example(s):</B>  
* <B>Counter-Example(s):</B>  
** [[Bottom-Up Hierarchical Clustering Algorithm]]/[[Agglomerative Clustering Algorithm]].
** [[Bottom-Up Hierarchical Clustering Algorithm]]/[[Agglomerative Clustering Algorithm]].

Revision as of 22:39, 23 March 2021

A Recursive Partitional Clustering Algorithm is a hierarchical clustering algorithm that is a top-down algorithm which partitions all of the data records immediately and then iteratively adjust them.



References

2009


  • (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Cluster_analysis#Hierarchical_clustering
    • Hierarchical clustering builds (agglomerative), or breaks up (divisive), a hierarchy of clusters. The traditional representation of this hierarchy is a tree (called a dendrogram), with individual elements at one end and a single cluster containing every element at the other. …

      … Cutting the tree at a given height will give a clustering at a selected precision. In the following example, cutting after the second row will yield clusters {a} {b c} {d e} {f}. Cutting after the third row will yield clusters {a} {b c} {d e f}, which is a coarser clustering, with a smaller number of larger clusters.



2003