Search Results for "multiple linear regression" - Page 2
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Showing 41 open source projects for "multiple linear regression"
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Yocto/GL
Yocto/GL: Tiny C++ Libraries for Data-Driven Physically-based Graphics
...See each header file for documentation. Simple shape data structure, utilities for manipulating triangle meshes, quads meshes and line sets, computation of normals and tangents, linear and Catmull-Clark subdivision, procedural shapes generation, ray intersection and closest point queries. Ray intersection and closest point queries of triangle meshes, quads meshes, line sets and shape instances using a two-level bounding volume hierarchy. Path tracing of surfaces and hairs supporting area and environment illumination, microfacet GGX and subsurface scattering, multiple importance sampling. -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results.... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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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... -
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LAMA
Heterogeneous Software Development Accelerated
...By using LAMA for their application, software developers benefit from higher productivity and stay up to date with the latest hardware innovations, both leading to shorter time-to-market. The framework supports multiple target platforms within a distributed heterogeneous environment. It offers optimized device code on the backend side, high scalability through latency hiding and asynchronous execution across multiple nodes. LAMA's modular and extensible software design supports the developer on several levels, regardless of whether writing his own portable code with the Heterogeneous Computing Development Kit or using prepared functionality from the Linear Algebra Package, the user always gains high productivity and maximum performance. -
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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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JChart2D
jchart2d is a real-time charting library written in java.
JChart2D is a easy to use component for displaying two- dimensional traces in a coordinate system written in Java. It supports real-time (animated) charting, custom trace rendering, Multithreading, viewports, automatic scaling and labels. Former UI controls (right click context menu, file menu) have been ported to the subproject jchart2d-uimenu (https://sourceforge.net/projects/jchart2d-uimenu.jchart2d.p/) for the benefit of having no dependencies to 3rd party libraries. -
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Fast Matrix for Java
General purpose matrix utilities for Java in Parallel Computing
Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors. -
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Statistics modules in Perl Data Language, with a quick-start guide for non-PDL people. They make the PDL shell work like R, but with PDL threading (fast automatic iteration) of procedures including t-test, linear regression, and k-means clustering.
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math toolkit
A C++ and Python library for finance, statistics and linear algebra.
A lightweight 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 ... ... -
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libfgen
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported. -
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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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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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Tesbo
Open source AI-powered test case management software.
Tesbo is an open source AI-powered test case management software built for QA teams. Tesbo's Context Engine reads your actual project requirements from Jira and Linear, existing test cases, product documentation, and defect history before generating a single test case. Every draft cites exactly which requirement, document, and defect shaped it. Nothing enters your repository without a QA engineer approving it first. The engine learns from every approval, edit, and rejection, so generated... -
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RenderStack is a support library for OpenGL 3+, currently in C++. Features currently for example basic window creation, mesh generation, wrappers for OpenGL programs, framebuffer, texture and vertex buffer objects. Predecessor: https://github.com/tksuoran/renderstack_net Successor: https://github.com/tksuoran/RenderStack
