Search Results for "vector linux"

ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects.

The JTS Topology Suite is an API for modelling and manipulating 2-dimensional linear geometry. It provides numerous geometric predicates and functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium.

Backport of C++11's std::string and std::vector to C. Other containers such as std::list, std::map, and std::set are in the works.

drvq is a C++ library implementation of dimensionality-recursive vector quantization, a fast vector quantization method in high-dimensional Euclidean spaces under arbitrary data distributions. It is an approximation of k-means that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter...

SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.

AVL Array is a sequence container (like std::vector or std::list) that allows fast insert/remove AND fast random access. Shiftable Files offers the usual file primitives plus fast insert/remove. Get the latest version via BZR in the Develop section.

x86mph is an optimized library with vector, matrix, and vertex helpers (including an own TnL) It also contains memory helpers, and other stuff such as image processing (color inverting, changing bpp) taking advantage of x86's 3DNow!, MMX, and SSE

A library of data structures with a unified API, written in portable C. Lists (uni- and bidirectional), a vector, a hash, a balanced tree (RB or AVL), a heap and tuples. Memory management, clone support, error handling.

A standalone, STL interface to the Torch library's Support Vector Machine (SVM). It supports single or multiclass (one vs. all) classification using dot product, polynomial, Gaussian and sigmoid kernels.