agglomerative


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ag·glom·er·ate

 (ə-glŏm′ə-rāt′)
tr. & intr.v. ag·glom·er·at·ed, ag·glom·er·at·ing, ag·glom·er·ates
To form or collect into a rounded mass.
adj. (-ər-ĭt)
Gathered into a rounded mass.
n. (-ər-ĭt)
1. A confused or jumbled mass; a heap.
2. A volcanic rock consisting of rounded and angular fragments fused together.

[Latin agglomerāre, agglomerāt-, to mass together : ad-, ad- + glomerāre, to form into a ball (from glomus, glomer-, ball).]

ag·glom′er·a′tive (-ə-rā′tĭv, -ər-ə-tĭv) adj.
ag·glom′er·a′tor n.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Adj.1.agglomerative - clustered together but not coherent; "an agglomerated flower head"
collective - forming a whole or aggregate
References in periodicals archive ?
Agglomerative Hierarchical Clustering (AHC) was done by using Pearson Correlation Coefficient and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) as Agglomeration method by XLSTAT 2012 version 1.02.
agglomerative factors--particularly information spillovers between
Elsewhere, coordinated inventory strategies for items in each cluster were determined using Genetic stepwise clustering and statistical agglomerative clustering methods [6].
Although other K-means clustering methods exist (e.g., extended K-means, agglomerative hierarchical, and fuzzy maximum likelihood), the fuzzy K-means clustering technique has been demonstrated to produce the most accurate results in reproducing the characteristics of input data (Duda and Canty 2002).
Agglomerative cluster analysis based on the Bray-Curtis similarity coefficients was also calculated and the similarities at 40 % and 75 % were overlain on the ordination.
An agglomerative, hierarchical cluster analysis was conducted on juvenile oyster data from each bar to determine whether particular groups of bars experienced similar juvenile oyster abundance.
ROCK (Guha, 1999), a Robust hierarchical-clustering algorithm is an agglomerative hierarchical clustering based on the notion of links.
In the agglomerative method of forming clusters, the computer generates clusters that get progressively larger, ultimately getting to a single large cluster comprising all cases.
Globalization has been accompanied by the assertion and reassertion of agglomerative tendencies in many different areas of the world.
This can be achieved by a simple agglomerative clustering method.
To overcome this, the proposed technique uses an agglomerative clustering algorithm to group the likelihood into a number of clusters, each representing similar groups of data, with a distinct state from the other clusters' data.