Search Results for "multiple linear regression" - Page 5
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Showing 167 open source projects for "multiple linear regression"
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LiVES
LiVES is a Video Editing System. It is designed to be simple to use, y
LiVES mixes realtime video performance and non-linear editing in one professional quality application. It is designed to be simple to use, yet powerful. It is small in size, yet it has many advanced features. Using LiVES, you can start editing and making video right away, without having to worry about formats, frame sizes, or framerates. It is a very flexible tool which is used by both professional VJ's and video editors - mix and switch clips from the keyboard, use dozens of realtime... -
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QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.
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Konbu Check
Linear constraint feasibility check and get program.
This program aims to check and gain a inner point from multiple set of linear constraints. This software works better in the case that range of variables are known and parameters are configured so. C++ and Eigen library needed, and to calculate more accurate, we may need mpfr++ library or, QD library. Freezed. -
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GSMLBook
Recipes for basic machine learning algorithms using sklearn in jupyter
...The emphasis is primarily on learning to use existing libraries such as Scikit-Learn with easy recipes and existing data files that can found on-line. Topics include linear, multilinear, polynomial, stepwise, lasso, ridge, and logistic regression; ROC curves and measures of binary classification; nonlinear regression (including an introduction to gradient descent); classification and regression trees; random forests; neural networks; probabilistic methods (KNN, naive Bayes', QDA, LDA); dimensionality reduction with PCA; support vector machines; and clustering with K-Means, hierarchical, and DBScan. ... -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
...The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and logistic regression to more complex techniques such as decision trees, support vector machines, clustering methods, and neural networks. Because the code avoids external machine learning libraries, it exposes the full logic behind model training, optimization, and prediction processes. The project also provides examples and explanations that illustrate how the algorithms behave and how different components interact during training. -
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Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2... -
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NUT Nutrition Software
nutrition software to record and analyze what you eat
nut is nutrition software to record what you eat and analyze your meals for nutrient composition. The emphasis is on personal dietary experimentation to determine the best possible diet. The software uses SQLite for a portable, os-independent application. -
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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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BigDecimal
Arithmetic and calculus with decimal numbers of arbitrary precision.
BigDecimal is a C # library that uses System.Numerics.BigInteger in its implementation, adding only a decimal place quantizer. In BigDecimal all the arithmetic operations are implemented, including, logarithms, systems resolution of linear equations, trigonometric functions, polynomial regression, hyperbolic functions, the notorious gamma function (factorial for non-integer real numbers) and more that will be implemented still. My intention is, at a minimum, to implement all the mathematical functions of the Windows calculator, and at most, if any, all the mathematical functions of Office Excel. -
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ADiGator
A MATLAB Automatic Differentiation Tool
...Furthermore, these calculations are written entirely in the native MATLAB language, and thus the process may be repeated to obtain nth order derivative files. The package is particularly appealing for applications where the same derivative must be found at multiple different points, i.e. non-linear root finding/optimization, stiff ode integration, etc. -
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plot.py
direct data plotting and evaluation
The Plot.py project tries to supply a measurement data visualization and treatment framework being easy to use while keeping the freedom for advanced users to execute additional data treatment algorithms. Plotting is done via gnuplot and the script used to produce the graphs can be exported for later use/changes. Many raw experimental data types (mostly of x-ray and neutron scattering experiments) are supported with more to be added on user request. The data treatment includes... -
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rene file renamer
Windows/Linux lexical/semantic multiple file renamer
Rene is an extended file renamer command line program written in Python for Windows and Linux. Its goal is to be easy to use but powerful. For basic use, the command syntax is as simple as Windows ren and Linux mv yet affords greater flexibility in reusing parts of the original name and formulating its replacement. Features include: -- Automatic name adjustment to avoid existing file names with a choice of parameterized collision avoidance schemas. -- Semantic name selection, for example,... -
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Retop Math Library
A Java Math Library for creating advanced programs
Regression Polynomial Regression Noise generator Advanced Matrix and Vector classes Physics Collisions Window to visualize functions -
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MOSGWA
genome wide association studies / Bayesian-type information criteria
MOSGWA is a tool for genome wide association studies (GWAS). It currently implements a search strategy using logistic regression and linear regression. -
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Win-Brash
A Windows Native Bourne Shell Interpreter
Win-Brash is a recoding, from scratch, of the Bourne shell as a native Microsoft Windows multi-threaded command line application. It uses Bourne shell syntax but recognizes Windows file names. The TAB key helps convert Unix style pathnames to fully valid windows pathnames. It also adds missing backslashes -- to reduce the need to always type two. For Documentation see: http://www.bordoon.com/brash To give brash.exe a try, use the download link to get winbrash-1.2.16.zip. Unzip... -
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BioPPSy
A biochemical property prediction system
...The program models a given property's dependence on a collection of molecular and structural descriptors using a training set of molecules. Neural networks and support vector regression are available, as well as linear models. The models generated by this analysis can then be used to predict the properties of compounds during the development of new and novel drugs. The program and its databases are all open-source. -
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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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L1-norm-robust-regression
linear regression on the basis of minimal absolute deviations error
This software provides a Fortran95 implemented routine to call and obtain the L1-norm regression coefficients. The "standard" linear regression minimizes the squared error. (L2-norm-regression). It allows for a simple solution process, hence its popularity. But it is not robust to outlier points. L1-norm regression is robust with respect to outliers but the solution algorithm is more difficult. It minimizes the sum of absolute deviations. -
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casync
Content-addressable data synchronization tool
A combination of the rsync algorithm and content-addressable storage. An efficient way to store and retrieve multiple related versions of large file systems or directory trees. An efficient way to deliver and update OS, VM, IoT and container images over the Internet in an HTTP and CDN friendly way. Let's take a large linear data stream, split it into variable-sized chunks (the size of each being a function of the chunk's contents), and store these chunks in individual, compressed files in some directory, each file named after a strong hash value of its contents, so that the hash value may be used to as key for retrieving the full chunk data. ... -
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H2O-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning
...The system operates as an in-memory computing platform that allows data scientists to train models quickly using distributed resources. It supports many machine learning algorithms including generalized linear models, gradient boosting machines, deep learning networks, and ensemble techniques. The platform provides interfaces for multiple programming languages such as Python, R, Java, and Scala, making it accessible to a wide range of developers and data scientists. H2O-3 integrates with big data technologies such as Hadoop and Apache Spark, enabling organizations to run machine learning workflows on large-scale data infrastructure. ... -
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JStats
JStats is a Java application/applet for statistical testing.
...The following tests are supported: * Parametric tests: T-test, ANOVA, Repeated Measures ANOVA * Non-parametric tests: Wilcoxon Rank-Sum, Wilcoxon Signed-Ranks, Kruskal-Wallis, Friedman * Check if datasets are normally distributed: Jarque-Bera, Shapiro-Wilk * Check if datasets have equal variances: F-test, Bartlett's test, John, Nagao and Sugiura's test * Correlation: Correlation coefficient, Spearman Rank correlation, linear regression * Confidence intervals test * Outliers: Generalized Extreme Studentized (ESD) test, outliers in ANOVA The latest version is available as applet on http://aiguy.org/Statistics.html -
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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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BRACIL-IA
Inference of Genome Accessibility in Bacteria from ChIP-seq data.
...Transcription factors need physical access to DNA it can potentially bind. However, prior to this work it was impossible to measure and assess DNA accessibility in bacteria. This code uses ChIP-seq from multiple experiments to infer the hidden variable for genome accessibility. This is performed by a linear mixed effect model that considers two parameters: DNA affinity and DNA accessibility. The fundaments for this code and its biological relevance is described in the following reference: Gomes ALC, Wang HH (2016) The Role of Genome Accessibility in Transcription Factor Binding in Bacteria. ... -
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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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Data Science Specialization
Course materials for the Data Science Specialization on Coursera
...The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow.
