Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.
In mathematics, computer science and especially graph theory, a distance matrix is a square matrix containing the distances, taken pairwise, between the elements of a set. Depending upon the application involved, the distance being used to define this matrix may or may not be a metric. If there are N elements, this matrix will have size N×N. In graph-theoretic applications, the elements are more often referred to as points, nodes or vertices.
In statistics, classification is the problem of identifying which of a set of categories (sub-populations) an observation belongs to. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient.
X-Video Motion Compensation (XvMC), is an extension of the X video extension (Xv) for the X Window System. The XvMC API allows video programs to offload portions of the video decoding process to the GPU video-hardware. In theory this process should also reduce bus bandwidth requirements. Currently, the supported portions to be offloaded by XvMC onto the GPU are motion compensation and inverse discrete cosine transform (iDCT) for MPEG-2 video. XvMC also supports offloading decoding of mo comp, iDCT, and VLD for not only MPEG-2 but also MPEG-4 ASP video on VIA Unichrome hardware.
VTune Profiler is a performance analysis tool for x86 based machines running Linux or Microsoft Windows operating systems. Many features work on both Intel and AMD hardware, but advanced hardware-based sampling requires an Intel-manufactured CPU.
Intel oneAPI DPC++/C++ Compiler and Intel C++ Compiler Classic are Intel’s C, C++, SYCL, and Data Parallel C++ (DPC++) compilers for Intel processor-based systems, available for Windows, Linux, and macOS operating systems.
Intel Integrated Performance Primitives is a multi-threaded software library of functions for multimedia and data processing applications, produced by Intel.
Intel Fortran Compiler, as part of Intel OneAPI HPC toolkit, is a group of Fortran compilers from Intel for Windows, macOS, and Linux.
Distance matrices are used in phylogeny as non-parametric distance methods and were originally applied to phenetic data using a matrix of pairwise distances. These distances are then reconciled to produce a tree. The distance matrix can come from a number of different sources, including measured distance or morphometric analysis, various pairwise distance formulae applied to discrete morphological characters, or genetic distance from sequence, restriction fragment, or allozyme data. For phylogenetic character data, raw distance values can be calculated by simply counting the number of pairwise differences in character states.
Video Acceleration API (VA-API) is an open source application programming interface that allows applications such as VLC media player or GStreamer to use hardware video acceleration capabilities, usually provided by the graphics processing unit (GPU). It is implemented by the free and open-source library libva, combined with a hardware-specific driver, usually provided together with the GPU driver.
Intel Parallel Studio XE was a software development product developed by Intel that facilitated native code development on Windows, macOS and Linux in C++ and Fortran for parallel computing. Parallel programming enables software programs to take advantage of multi-core processors from Intel and other processor vendors.
Intel Inspector is a memory and thread checking and debugging tool to increase the reliability, security, and accuracy of C/C++ and Fortran applications.
The following outline is provided as an overview of and topical guide to regression analysis:
Intel oneAPI Math Kernel Library is a library of optimized math routines for science, engineering, and financial applications. Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math.
Revolution Analytics is a statistical software company focused on developing open source and "open-core" versions of the free and open source software R for enterprise, academic and analytics customers. Revolution Analytics was founded in 2007 as REvolution Computing providing support and services for R in a model similar to Red Hat's approach with Linux in the 1990s as well as bolt-on additions for parallel processing. In 2009 the company received nine million in venture capital from Intel along with a private equity firm and named Norman H. Nie as their new CEO. In 2010 the company announced the name change as well as a change in focus. Their core product, Revolution R, would be offered free to academic users and their commercial software would focus on big data, large scale multiprocessor computing, and multi-core functionality.
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since.
The following outline is provided as an overview of and topical guide to machine learning:
