ghc-hierarchical-clustering

This package provides a function to create a dendrogram from a list of items
and a distance function between them. Initially a singleton cluster is created
for each item, and then new, bigger clusters are created by merging the two
clusters with least distance between them. The distance between two clusters is
calculated according to the linkage type. The dendrogram represents not only
the clusters but also the order on which they were created.
This package has many implementations with different performance
characteristics. There are SLINK and CLINK algorithm implementations that are
optimal in both space and time. There are also naive implementations using a
distance matrix. Using the 'dendrogram' function from
'Data.Clustering.Hierarchical' automatically chooses the best implementation we
have.
Changes in version 0.4:

Specialize the distance type to Double for efficiency reasons. It's uncommon

to use distances other than Double.

Implement SLINK and CLINK. These are optimal algorithms in both space and

time for single and complete linkage, respectively, running in /O(n^2)/ time
and /O(n)/ space.

Reorganized internal implementation.

Some performance improvements for the naive implementation.

Better test coverage. Also, performance improvements for the test suite, now


running in 3 seconds (instead of one minute).
Changes in version 0.3.1.2 (version 0.3.1.1 was skipped):

Added tests for many things. Use 'cabal test' =).

Changes in version 0.3.1:

Works with containers 0.4 (thanks, Doug Beardsley).

Removed some internal unnecessary overheads and added some strictness.


Changes in version 0.3.0.1:

Listed changes of unreleased version 0.2.

Changes in version 0.3:

Added function 'cutAt'.

Fixed complexity in Haddock comments.


Changes in version 0.2:

Added function 'elements'.

Added separate functions for each linkage type. This may be useful if you


want to create a dendrogram and your distance data type isn't an instance of
'Floating'.

          

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License: BSD-3-Clause
URL: https://hackage.haskell.org/package/hierarchical-clustering