|
r-xmlparsedata
|
public |
Convert the output of 'utils::getParseData()' to an 'XML' tree, that one can search via 'XPath', and easier to manipulate in general.
|
2025-04-22 |
|
r-ggmcmc
|
public |
Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables.
|
2025-04-22 |
|
autoconf-archive
|
public |
Collection of over 500 reusable autoconf macros
|
2025-04-22 |
|
intel-vaapi-driver
|
public |
VA-API (Video Acceleration API) user mode driver for Intel GEN Graphics family
|
2025-04-22 |
|
intel-hybrid-driver
|
public |
VA driver for Intel G45 & HD Graphics family
|
2025-04-22 |
|
cmrt
|
public |
Media GPU kernel manager for Intel G45 & HD Graphics family
|
2025-04-22 |
|
libva
|
public |
Libva is an implementation for VA-API (Video Acceleration API)
|
2025-04-22 |
|
r-juniperkernel
|
public |
Provides a full implementation of the 'Jupyter' <http://jupyter.org/> messaging protocol in C++ by leveraging 'Rcpp' and 'Xeus' <https://github.com/QuantStack/xeus>. 'Jupyter' supplies an interactive computing environment and a messaging protocol defined over 'ZeroMQ' for multiple programming languages. This package implements the 'Jupyter' kernel interface so that 'R' is exposed to this interactive computing environment. 'ZeroMQ' functionality is provided by the 'pbdZMQ' package. 'Xeus' is a C++ library that facilitates the implementation of kernels for 'Jupyter'. Additionally, 'Xeus' provides an interface to libraries that exist in the 'Jupyter' ecosystem for building widgets, plotting, and more <https://blog.jupyter.org/interactive-workflows-for-c-with-jupyter-fe9b54227d92>. 'JuniperKernel' uses 'Xeus' as a library for the 'Jupyter' messaging protocol.
|
2025-04-22 |
|
seccomp
|
public |
libseccomp provides an easy to use, platform independent, interface to the Linux syscall filtering mechanism.
|
2025-04-22 |
|
libseccomp
|
public |
libseccomp provides an easy to use, platform independent, interface to the Linux syscall filtering mechanism.
|
2025-04-22 |
|
r-whoami
|
public |
Look up the username and full name of the current user, the current user's email address and 'GitHub' username, using various sources of system and configuration information.
|
2025-04-22 |
|
r-bfa
|
public |
Provides model fitting for several Bayesian factor models including Gaussian, ordinal probit, mixed and semiparametric Gaussian copula factor models under a range of priors.
|
2025-04-22 |
|
libsharp
|
public |
Library for fast spherical harmonic transforms, see http://arxiv.org/abs/1303.4945
|
2025-04-22 |
|
calculix
|
public |
3D Structural Finite Element Program
|
2025-04-22 |
|
tzcode
|
public |
The Time Zone Database (often called tz or zoneinfo) code
|
2025-04-22 |
|
lzip
|
public |
Lzip is a lossless data compressor with a user interface similar to the one of gzip or bzip2.
|
2025-04-22 |
|
fribidi
|
public |
The Free Implementation of the Unicode Bidirectional Algorithm.
|
2025-04-22 |
|
mpi4py-fft
|
public |
Fast Fourier Transforms (FFTs) in parallel with MPI for Python
|
2025-04-22 |
|
wntr
|
public |
Water Network Tool for Resilience
|
2025-04-22 |
|
hyperspy-dev
|
public |
Multi-dimensional data analysis
|
2025-04-22 |
|
hyperspy-base
|
public |
Multi-dimensional data analysis
|
2025-04-22 |
|
bsddb3
|
public |
Python bindings for Oracle Berkeley DB
|
2025-04-22 |
|
r-collateral
|
public |
The purrr package allows you to capture the side effects (errors, warning, messages and other output) of functions using safely() and quietly(). Using collateral, you can quickly see which elements of a list (or list-column) returned results, which threw errors and which returned warnings or other output.
|
2025-04-22 |
|
r-iml
|
public |
Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) <arXiv:1801.01489>, accumulated local effects plots described by Apley (2018) <arXiv:1612.08468>, partial dependence plots described by Friedman (2001) <http://www.jstor.org/stable/2699986>, individual conditional expectation ('ice') plots described by Goldstein et al. (2013) <doi:10.1080/10618600.2014.907095>, local models (variant of 'lime') described by Ribeiro et. al (2016) <arXiv:1602.04938>, the Shapley Value described by Strumbelj et. al (2014) <doi:10.1007/s10115-013-0679-x>, feature interactions described by Friedman et. al <doi:10.1214/07-AOAS148> and tree surrogate models.
|
2025-04-22 |
|
r-metrics
|
public |
An implementation of evaluation metrics in R that are commonly used in supervised machine learning. It implements metrics for regression, time series, binary classification, classification, and information retrieval problems. It has zero dependencies and a consistent, simple interface for all functions.
|
2025-04-22 |
