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libterralib3t64
C++ library for Geographical Information Systems
TerraLib enables quick development of custom-built geographical applications
using spatial databases. As a research tool, TerraLib is aimed at providing a
rich and powerful environment for the development of GIS research,
enabling the development of GIS prototypes that include new concepts such as
spatio-temporal data models, geographical ontologies and advanced spatial
analysis techniques. TerraLib defines a geographical data model and provides
support for this model over a range of different DBMS (MySQL, PostgreSQL,
ORACLE and ACCESS), and is implemented as a library of C++ classes and
functions, written in ANSI-C++.
libllvmspirvlib17
bi-directional translator for LLVM/SPIRV -- shared library
SPIRV-LLVM-translator is a LLVM/SPIRV bi-directional translator. This
package includes a library and a tool for translation between LLVM IR
and SPIR-V.
libghc-hslua-module-zip-prof
Lua module to work with file zips; profiling libraries
Module with functions for creating, modifying, and extracting files from zip
archives.
libghc-hslua-module-doclayout-prof
Lua module wrapping Text.DocLayout; profiling libraries
Lua module wrapping the doclayout Haskell package.
tntdb-sqlite5
SQLite backend for tntdb database access library
This library provides a thin, database independent layer over an SQL
database. It lacks complex features like schema queries or wrapper
classes like active result sets or data bound controls. Instead you
get to access the database directly with SQL queries. The library is
suited for application programming, not for writing generic database
handling tools.
r-cran-rose
GNU R random over-sampling examples
Functions to deal with binary classification
problems in the presence of imbalanced classes. Synthetic balanced samples are
generated according to ROSE (Menardi and Torelli, 2013).
Functions that implement more traditional remedies to the class imbalance
are also provided, as well as different metrics to evaluate a learner accuracy.
These are estimated by holdout, bootstrap or cross-validation methods.