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Description

Fast and Robust Hierarchical Clustering with Noise Point Detection.

The Genie algorithm (Gagolewski, 2021 <DOI:10.1016/j.softx.2021.100722>) is a robust and outlier-resistant hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <DOI:10.1016/j.ins.2016.05.003>). This package features its faster and more powerful version. It allows clustering with respect to mutual reachability distances, enabling it to act as a noise point detector or a version of 'HDBSCAN*' that can identify a predefined number of clusters. The package also features an implementation of the Gini and Bonferroni inequality indices, external cluster validity measures (e.g., the normalised clustering accuracy, the adjusted Rand index, the Fowlkes-Mallows index, and normalised mutual information), and internal cluster validity indices (e.g., the Calinski-Harabasz, Davies-Bouldin, Ball-Hall, Silhouette, and generalised Dunn indices). The 'Python' version of 'genieclust' is available via 'PyPI'.
Metadata

Version

1.2.0

License

Unknown

Platforms (75)

    Darwin
    FreeBSD
    Genode
    GHCJS
    Linux
    MMIXware
    NetBSD
    none
    OpenBSD
    Redox
    Solaris
    WASI
    Windows
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