Search Results for "multiple regression"
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Showing 13 open source projects for "multiple regression"
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Selenium
Browser automation framework and ecosystem
...If you want to scale by distributing and running tests on several machines and manage multiple environments from a central point. -
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Passmark
The open-source Playwright library for AI browser regression testing
...This approach significantly reduces reliance on AI during repeated test executions, improving both performance and cost efficiency. The framework also incorporates multi-model validation, using multiple AI systems to verify assertions and reduce the risk of incorrect results. -
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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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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming... -
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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5
Gatling
Modern Load Testing as Code
Gatling is a high-performance load testing tool built on the JVM that emphasizes realism, scalability, and developer ergonomics. Test scenarios are scripted in a concise Scala-based DSL, allowing you to model user journeys with think times, feeders (dynamic data), checks, and assertions all in code. Its asynchronous, non-blocking engine (backed by Netty) can drive very high concurrency from a single injector, reducing the need for large injector farms. Gatling supports HTTP out of the box as... -
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FlowLens MCP
Open-source MCP server that gives your coding agent
FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console... -
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SCons
A software construction tool
SCons is a software construction tool that is a superior alternative to the classic "Make" build tool that we all know and love. SCons is implemented as a Python script and set of modules, and SCons "configuration files" are actually executed as Python scripts. This gives SCons many powerful capabilities not found in other software build tools. We make SCons available in three distinct packages, for different purposes. - The scons package is the basic package to install SCons. You... -
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uuv e2e accessibility testing
Open-source platform for automated accessibility testing.
UUV is an open-source platform that automates accessibility testing for web. It helps development, QA, and accessibility teams detect accessibility issues early, improve software quality, and maintain compliance with standards such as WCAG, RGAA, RAWEB. The UUV Desktop Assistant allows users to inspect UI elements, verify accessibility properties, and automatically generate reusable Gherkin scenarios and accessibility assertions. Test execution produces detailed reports with errors,... -
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FluentLenium
FluentLenium is a web & mobile automation framework
...FluentLenium is shipped with adapters for JUnit4, JUnit5, TestNG, Spock, Spring TestNG, Cucumber and Kotest, but it can also be used standalone. FluentLenium best integrates with AssertJ, but you can also choose to use the assertion framework you want. FluentLenium gives you multiple methods which help you write tests quicker. All those methods are tested daily by commercial regression test suites maintained by project developers. -
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main... -
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and extensive documentation and a wiki help fill in the details. The Accord.NET project provides... -
12
Diffy
Find potential bugs in your services with Diffy
Diffy is a traffic-shadowing and response-diffing tool that helps you validate a new version of a service against a trusted baseline before a full cutover. It acts as a proxy that fans out real production requests to three backends: the current “primary,” a “candidate” (new build), and a “shadow” baseline, then compares responses to detect behavioral differences. By using live traffic rather than synthetic tests, Diffy surfaces edge cases and data-dependent discrepancies that unit tests... -
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A task for the Apache "Ant" build system. The "mtxslt" (multi-XSLT) task extends the standard Ant "xslt/style" task to make it easy to use multiple XSLT engines during the same build. This is useful for regression testing of XSLT scripts against
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