| Name : R-DataVisualizations
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| Version : 1.3.2
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : 2.5
| Date : 2024-08-29 00:26:49
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| Group : Development/Libraries/Other
| Source RPM : R-DataVisualizations-1.3.2-2.5.src.rpm
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| Size : 3.11 MB
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| Packager : (none)
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| Summary : Visualizations of High-Dimensional Data
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Description :
Gives access to data visualisation methods that are relevant from the
data scientist\'s point of view. The flagship idea of
\'DataVisualizations\' is the mirrored density plot (MD-plot) for either
classified or non-classified multivariate data published in Thrun, M.C.
et al.: \"Analyzing the Fine Structure of Distributions\" (2020), PLoS
ONE, < DOI:10.1371/journal.pone.0238835>. The MD-plot outperforms the
box-and-whisker diagram (box plot), violin plot and bean plot and
geom_violin plot of ggplot2. Furthermore, a collection of various
visualization methods for univariate data is provided. In the case of
exploratory data analysis, \'DataVisualizations\' makes it possible to
inspect the distribution of each feature of a dataset visually through
a combination of four methods. One of these methods is the Pareto
density estimation (PDE) of the probability density function (pdf).
Additionally, visualizations of the distribution of distances using
PDE, the scatter-density plot using PDE for two variables as well as
the Shepard density plot and the Bland-Altman plot are presented here.
Pertaining to classified high-dimensional data, a number of
visualizations are described, such as f.ex. the heat map and silhouette
plot. A political map of the world or Germany can be visualized with
the additional information defined by a classification of countries or
regions. By extending the political map further, an uncomplicated
function for a Choropleth map can be used which is useful for
measurements across a geographic area. For categorical features, the
Pie charts, slope charts and fan plots, improved by the ABC analysis,
become usable. More detailed explanations are found in the book by
Thrun, M.C.: \"Projection-Based Clustering through Self-Organization and
Swarm Intelligence\" (2018) < DOI:10.1007/978-3-658-20540-9>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/x86_64 |
