ELKI and Single-linkage clustering

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between ELKI and Single-linkage clustering

ELKI vs. Single-linkage clustering

ELKI (for Environment for DeveLoping KDD-Applications Supported by Index-Structures) is a knowledge discovery in databases (KDD, "data mining") software framework developed for use in research and teaching originally at the database systems research unit of Professor Hans-Peter Kriegel at the Ludwig Maximilian University of Munich, Germany. In statistics, single-linkage clustering is one of several methods of hierarchical clustering.

Similarities between ELKI and Single-linkage clustering

ELKI and Single-linkage clustering have 1 thing in common (in Unionpedia): Hierarchical clustering.

Hierarchical clustering

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.

ELKI and Hierarchical clustering · Hierarchical clustering and Single-linkage clustering · See more »

The list above answers the following questions

What ELKI and Single-linkage clustering have in common
What are the similarities between ELKI and Single-linkage clustering

ELKI and Single-linkage clustering Comparison

ELKI has 82 relations, while Single-linkage clustering has 9. As they have in common 1, the Jaccard index is 1.10% = 1 / (82 + 9).

References

This article shows the relationship between ELKI and Single-linkage clustering. To access each article from which the information was extracted, please visit:

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