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Rattan. Calamus thwaitesii in southwestern India. Juvenile Calamus oblongus subsp. mollis in a forest understory in the Philippines. Rattan, also spelled ratan (from Malay: rotan), is the name for roughly 600 species of Old World climbing palms belonging to subfamily Calamoideae. The greatest diversity of rattan palm species and genera are in ...
Korthalsia is a clustering genus of flowering plant in the palm family spread throughout Southeast Asia.It is a highly specialized rattan with some species known to have an intimate relationship with ants, hence the common name ant rattan. [2]
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical ...
In the theory of cluster analysis, the nearest-neighbor chain algorithm is an algorithm that can speed up several methods for agglomerative hierarchical clustering. These are methods that take a collection of points as input, and create a hierarchy of clusters of points by repeatedly merging pairs of smaller clusters to form larger clusters.
Complete-linkage clustering. Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. At the beginning of the process, each element is in a cluster of its own. The clusters are then sequentially combined into larger clusters until all elements end up being in the same cluster.
q. -flats. In data mining and machine learning, k q -flats algorithm [1][2] is an iterative method which aims to partition m observations into k clusters where each cluster is close to a q -flat, where q is a given integer. It is a generalization of the k -means algorithm.
In statistics, cluster analysis is the algorithmic grouping of objects into homogeneous groups based on numerical measurements. Model-based clustering[1] bases this on a statistical model for the data, usually a mixture model. This has several advantages, including a principled statistical basis for clustering, and ways to choose the number of ...
Biclustering, block clustering, [1] [2] Co-clustering or two-mode clustering [3] [4] [5] is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin [ 6 ] to name a technique introduced many years earlier, [ 6 ] in 1972, by John A. Hartigan .