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inaparc

Initialization Algorithms for Partitioning Cluster Analysis

v1.2.1 · Sep 13, 2025 · GPL (>= 2)

Description

Partitioning clustering algorithms divide data sets into k subsets or partitions so-called clusters. They require some initialization procedures for starting the algorithms. Initialization of cluster prototypes is one of such kind of procedures for most of the partitioning algorithms. Cluster prototypes are the centers of clusters, i.e. centroids or medoids, representing the clusters in a data set. In order to initialize cluster prototypes, the package 'inaparc' contains a set of the functions that are the implementations of several linear time-complexity and loglinear time-complexity methods in addition to some novel techniques. Initialization of fuzzy membership degrees matrices is another important task for starting the probabilistic and possibilistic partitioning algorithms. In order to initialize membership degrees matrices required by these algorithms, a number of functions based on some traditional and novel initialization techniques are also available in the package 'inaparc'.

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14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (3)

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Dependency Network

Dependencies Reverse dependencies kpeaks lhs MapperAlgo ppclust Evacluster inaparc

Version History

new 1.2.1 Mar 10, 2026
updated 1.2.1 ← 1.2.0 diff Sep 13, 2025
updated 1.2.0 ← 1.1.0 diff Jun 15, 2022
updated 1.1.0 ← 0.2.0 diff Feb 7, 2020
updated 0.2.0 ← 0.1.0 diff Nov 4, 2017
new 0.1.0 Oct 15, 2017