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divisiv

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The answer DIVISIV has 0 possible clue(s) in existing crosswords.

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The word DIVISIV is NOT valid in any word game. (Sorry, you cannot play DIVISIV in Scrabble, Words With Friends etc)

There are 7 letters in DIVISIV ( D2I1S1V4 )

To search all scrabble anagrams of DIVISIV, to go: DIVISIV?

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Scrabble results that can be created with an extra letter added to DIVISIV

DIVISIVE

5 letters out of DIVISIV

VIVID

4 letters out of DIVISIV

VIDS

3 letters out of DIVISIV

DIS IDS VID VIS

2 letters out of DIVISIV

ID IS SI

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Definitions of divisiv in various dictionaries:

DIVISIV - In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks...

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Divisiv might refer to
In data mining and statistics, Hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types:
* Agglomerative: This is a "bottom up" approach: each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy.
* Divisive: This is a "top down" approach: all observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.In general, the merges and splits are determined in a greedy manner. The results of hierarchical clustering are usually presented in a dendrogram.
* The standard algorithm for hierarchical agglomerative clustering (HAC) has a time complexity of
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* {\displaystyle {\mathcal {O}}(n^{3})}
* and requires
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* memory, which makes it too slow for even medium data sets. However, for some special cases, optimal efficient agglomerative methods (of complexity
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* ) are known: SLINK for single-linkage and CLINK for complete-linkage clustering. With a heap the runtime of the general case can be reduced to
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* {\displaystyle {\mathcal {O}}(n^{2}\log n)}
* at the cost of further increasing the memory requirements. In many programming languages, the memory overheads of this approach are too large to make it practically usable.
* Except for the special case of single-linkage, none of the algorithms (except exhaustive search in
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* ) can be guaranteed to find the optimum solution.
* Divisive clustering with an exhaustive search is
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* , but it is common to use faster heuristics to choose splits, such as k-means.
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