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This package provides a small collection of interesting and educational machine learning data sets which are used as examples in the mlr3 book Applied machine learning using mlr3 in R https://mlr3book.mlr-org.com, the use case gallery https://mlr3gallery.mlr-org.com, or in other examples. All data sets are properly preprocessed and ready to be analyzed by most machine learning algorithms. Data sets are automatically added to the dictionary of tasks if mlr3 is loaded.
This package provides an alternative to R's built-in functionality for handling regular expressions, based on the Onigmo library. It offers first-class compiled regex objects, partial matching and function-based substitutions, amongst other features.
This package provides JSON parsing capability through the Rapidjson library.
Circular Statistics, from "Topics in Circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.
This package enables the use of emoji and the Font Awesome glyphs in both base and ggplot2 graphics.
This package provides a model agnostic tool for decomposition of predictions from black boxes. It supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models.
This package can compute multivariate normal and t-probabilities, quantiles, random deviates and densities.
This package provides gradient projection algorithms for factor rotation. For details see ?GPArotation.
This package provides functionality to benchmark your CPU and compare against other CPUs. Also provides functions for obtaining system specifications, such as RAM, CPU type, and R version.
The brew package implements a templating framework for mixing text and R code for report generation. The template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module.
This package provides classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
This package provides a common framework for optimization of black-box functions for other packages, e.g. mlr3. It offers various optimization methods e.g. grid search, random search and generalized simulated annealing.
The biglm package lets you create a linear model object that uses only codep^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory.
This package provides an extension of the functionality of the Matrix package for using sparse matrices. Some of the functions are very general, while other are highly specific for the special data format used for quantitative language comparison (QLC).
This package provides chronological R objects which can handle dates and times.
This package provides streamlined data import and export infrastructure by making assumptions that the user is probably willing to make: import and export determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., stringsAsFactors=FALSE), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, convert, provides a simple method for converting between file types.
This package provides simple, flexible assertions on data.frame or data.table objects with verbose output for vetting. While other assertion packages apply towards more general use-cases, assertable is tailored towards tabular data. It includes functions to check variable names and values, whether the dataset contains all combinations of a given set of unique identifiers, and whether it is a certain length. In addition, assertable includes utility functions to check the existence of target files and to efficiently import multiple tabular data files into one data.table.
UpSet plots are an improvement over Venn Diagram for set overlap visualizations. Striving to bring the best of the UpSetR and ggplot2, this package offers a way to create complex overlap visualisations, using simple and familiar tools.
Functions to help implement the extraction / subsetting / indexing function [ and replacement function [<- of custom matrix-like types (based on S3, S4, etc.), modeled as closely to the base matrix class as possible (with tests to prove it).
This package provides an interface to Amazon Web Services application integration services, including Simple Queue Service (SQS) message queue, Simple Notification Service (SNS) publish/subscribe messaging, and more.
This package provides tools for the computation of matrix and scalar exponentiation.
This package provides a set of R bindings for the Selenium 2.0 WebDriver (see https://selenium.dev/documentation/en/ for more information) using the JsonWireProtocol (see https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol for more information). Selenium 2.0 WebDriver allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.
This package provides implementations of a family of Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear models.
This package provides a suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.