Search Results for "regression"
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Showing 16 open source projects for "regression"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Selenium
Browser automation framework and ecosystem
...Primarily it is for automating web applications for testing purposes, but is certainly not limited to just that. Boring web-based administration tasks can (and should) also be automated as well. If you want to create robust, browser-based regression automation suites and tests, scale and distribute scripts across many environments, then you want to use Selenium WebDriver, a collection of language specific bindings to drive a browser - the way it is meant to be driven. If you want to create quick bug reproduction scripts, create scripts to aid in automation-aided exploratory testing, then you want to use Selenium IDE; a Chrome and Firefox add-on that will do simple record-and-playback of interactions with the browser. ... -
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XGBoost
Scalable and Flexible Gradient Boosting
XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. ... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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OculiX
Visual Automation IDE — automate anything you see on screen
...Key features: - Guided step-by-step recorder with live code preview - Image recognition via OpenCV 4.10 - Dual OCR: Tesseract (built-in) + PaddleOCR (neural, high precision) - Local and remote automation via integrated VNC - SSH tunnels via embedded JSch - Cross-platform: Windows, macOS (Apple Silicon M1-M4), Linux - Scripting: Jython, JRuby, Java, PowerShell, AppleScript - Java 17 recommended (Java 8+ supported) - Full CI/CD with automated builds for all platforms Used worldwide for test automation, RPA, and visual regression testing. MIT License. Maintained by oculix-org. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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stkpp
C++ Statistical ToolKit
STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template classes in C++ and is suitable for projects ranging from small one-off projects to complete data mining application suites. -
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glslmath
C++ header-only library that simulates GLSL math
GLSLmath provides C++ math operations as defined by GLSL. For example, it provides methods to easily setup viewing transformations and perspective projections. GLSLmath has been inspired by the glm and slmath libraries, which aim to mimic GLSL, but in contrast to those GLSLmath does not focus on a complete conforming implementation of GLSL. It rather aims to provide a convenient single header file that implements the most commonly used subset of GLSL so that it is easy to use for rapid... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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bigz
Simple and complete bignum/rational C library with wrappers for C++
bigz is the continuation of an old BigNum project that started its life as a joined INRIA & Dec project in 1989. The current version includes many fixes and improvements. Although not as efficient as, say gmp, it is very small, reasonably efficient and extremely portable. -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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HHVM
A virtual machine for executing programs written in Hack
...HHVM uses a just-in-time (JIT) compilation approach to achieve great runtime performance while maintaining amazing development flexibility. HHVM supports the Hack programming language. We are moving fast, making changes daily and releasing often. If you notice a regression in the typechecker or the runtime, please open issues when you find them. Rather than directly interpret or compile source code directly to C++, HHVM compiles Hack into an intermediate bytecode. This bytecode is then translated into x64 machine code dynamically at runtime by a just-in-time (JIT) compiler. This compilation process allows for all sorts of optimizations that cannot be made in a statically compiled binary, thus enabling higher performance of your Hack programs. -
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CURRENNT
CUDA-enabled machine learning library for recurrent neural networks
CURRENNT is a machine learning library for Recurrent Neural Networks (RNNs) which uses NVIDIA graphics cards to accelerate the computations. The library implements uni- and bidirectional Long Short-Term Memory (LSTM) architectures and supports deep networks as well as very large data sets that do not fit into main memory. -
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Regression Suite
Test suite with unit regrssion and execution statistics
RegressionSuite is a software test suite that incorporates measurement of the startup lag, measurement of accurate execution times, generating execution statistics, customized input distributions, and processable regression specific details as part of the regular unit tests. Essentially, RegressionSuite provides the frame-work around which the individual unit regressors are invoked (and details and statistics collected). Unit regressors are grouped into named regressor sets (or modules), and regressors are created by implementing specific regressor interfaces. ... -
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math toolkit
A C++ and Python library for finance, statistics and linear algebra.
...Finance features include compound rate present/future value, annuity, various present/future value coefficients ... Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... And some auxiliary features like random number generators, equation solution, numerical integration, permutation/combination and gcd/lcm etc. ... -
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AIS is an Development Platform providing a high-speed JIT compiler for LISP and JavaScript, web server, object repositories, MySQL integration and libraries supporting a wide variety of advanced genetic programming and symbolic regression techniques.
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Library that will supply a clean interface for Linear, Quadratic, and Logarithmic regressions including verification for autocorrelation and heteroscedasticity using Durbin Watson and White tests.
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FlashTestXpress is a tool to help on performing repeated tests of applications using Oracle as a database backend. Thus it can be used in regression testing scenarios.
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