libqgis-native3.34.13

QGIS - shared native gui library

QGIS is a Geographic Information System (GIS) which manages, analyzes and display databases of geographic information.

libmkl-gf

Intel® MKL: (ia32) Interface library for the GNU Fortran compiler

Intel® Math Kernel Library (Intel® MKL) is a computing math library of highly optimized, extensively threaded routines for applications that require maximum performance.
Debian Sid - Qtile 0.10.6

qtile

Small, simple, extensible X11 window manager written in Python

Qtile is: * simple, small and extensible. It's easy to write your own layouts, widgets and built-in commands. * configured entirely in Python. * command-line shell that allows all aspects of Qtile to be manipulated and inspected. * complete remote scriptability - write scripts to set up workspaces, manipulate windows, update status bar widgets and more. * unit tested. Qtile's scriptability has made thorough unit testing possible, making it one of the best-tested window managers around.

r-cran-cpp11

C++11 interface for GNU R's C interface

Provides a header only, C++11 interface to R's C interface. Compared to other approaches 'cpp11' strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with 'ALTREP' vectors.

libcreaterepo-c1

library for creating RPM repository metadata

The createrepo tool generates the repodata directory and XML metadata that makes up a repository of RPM packages. This repository format is supported by apt-rpm, red-carpet(zen), smartpm, up2date, yast, and yum.

r-cran-mlr

Machine learning in GNU R

Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.