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Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering
Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software,
Fast and Simple 'MongoDB' Client for R
High-performance MongoDB client based on 'mongo-c-driver' and 'jsonlite'. Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication, and GridFS. The online user manual provides an overview of the available methods in the package: < https://jeroen.github.io/mongolite/>.
Convenience Functions for Arrays
Some convenient functions to work with arrays.
C5.0 Decision Trees and Rule-Based Models
C5.0 decision trees and rule-based models for pattern recognition that extend the work of Quinlan (1993, ISBN:1-55860-238-0).
A Toolbox for Manipulating and Assessing Colors and Palettes
Carries out mapping between assorted color spaces including RGB, HSV, HLS,
CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB, and polar CIELAB.
Qualitative, sequential, and diverging color palettes based on HCL colors
are provided along with corresponding ggplot2 color scales.
Color palette choice is aided by an interactive app (with either a Tcl/Tk
or a shiny graphical user interface) and shiny apps with an HCL color picker and a
color vision deficiency emulator. Plotting functions for displaying
and assessing palettes include color swatches, visualizations of the
HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation
functions include: desaturation, lightening/darkening, mixing, and
simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly).
Details can be found on the project web page at < https://colorspace.R-Forge.R-project.org/>
and in the accompanying scientific paper: Zeileis et al. (2020, Journal of Statistical
Software,
Extreme Gradient Boosting
Extreme Gradient Boosting, which is an efficient implementation
of the gradient boosting framework from Chen & Guestrin (2016)
Generate Useful ROC Curve Charts for Print and Interactive Use
Most ROC curve plots obscure the cutoff values and inhibit interpretation and comparison of multiple curves. This attempts to address those shortcomings by providing plotting and interactive tools. Functions are provided to generate an interactive ROC curve plot for web use, and print versions. A Shiny application implementing the functions is also included.
Analysis of Dose-Response Curves
Analysis of dose-response data is made available through a suite of flexible and versatile model fitting and after-fitting functions.
R Interface to NLopt
Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See < https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/> for more information on the available algorithms. Building from included sources requires 'CMake'. On Linux and 'macOS', if a suitable system build of NLopt (2.7.0 or later) is found, it is used; otherwise, it is built from included sources via 'CMake'. On Windows, NLopt is obtained through 'rwinlib' for 'R <= 4.1.x' or grabbed from the appropriate toolchain for 'R >= 4.2.0'.
Provides Access to Git Repositories
Interface to the 'libgit2' library, which is a pure C implementation of the 'Git' core methods. Provides access to 'Git' repositories to extract data and running some basic 'Git' commands.