パッケージ: r-cran-genieclust (1.0.0-1)
r-cran-genieclust に関するリンク
Trisquel の資源:
r-cran-genieclust ソースパッケージをダウンロード:
- [r-cran-genieclust_1.0.0-1.dsc]
- [r-cran-genieclust_1.0.0.orig.tar.gz]
- [r-cran-genieclust_1.0.0-1.debian.tar.xz]
メンテナ:
Original Maintainers:
- Debian R Packages Maintainers
- Andreas Tille
外部の資源:
- ホームページ [cran.r-project.org]
類似のパッケージ:
GNU R Genie++ Hierarchical Clustering Algorithm with Noise Points Detection
A retake on the Genie algorithm - a robust hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <DOI:10.1016/j.ins.2016.05.003>). Now faster and more memory efficient; determining the whole hierarchy for datasets of 10M points in low dimensional Euclidean spaces or 100K points in high-dimensional ones takes only 1-2 minutes. Allows clustering with respect to mutual reachability distances so that it can act as a noise point detector or a robustified version of 'HDBSCAN*' (that is able to detect a predefined number of clusters and hence it does not dependent on the somewhat fragile 'eps' parameter).
The package also features an implementation of economic inequity indices (the Gini, Bonferroni index) and external cluster validity measures (partition similarity scores; e.g., the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, pair sets index).
See also the 'Python' version of 'genieclust' available on 'PyPI', which supports sparse data, more metrics, and even larger datasets.
その他の r-cran-genieclust 関連パッケージ
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- dep: libc6 (>= 2.29)
- GNU C Library: Shared libraries
以下のパッケージによって提供される仮想パッケージでもあります: libc6-udeb
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- dep: libgcc-s1 (>= 3.3.1) [armhf 以外]
- GCC support library
- dep: libgcc-s1 (>= 3.5) [armhf]
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- dep: libgomp1 (>= 4.9)
- GCC OpenMP (GOMP) support library
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- dep: libstdc++6 (>= 5.2) [armhf]
- GNU Standard C++ Library v3
- dep: libstdc++6 (>= 9) [armhf 以外]
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- dep: r-api-4.0
- 以下のパッケージによって提供される仮想パッケージです: r-base-core
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- dep: r-base-core (>= 4.1.1-2)
- GNU R core of statistical computation and graphics system
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- dep: r-cran-rcpp (>= 1.0.4)
- GNU R package for Seamless R and C++ Integration