Search Results for "multi linear regression"
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Showing 166 open source projects for "multi linear regression"
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Calmerry is beneficial for businesses of all sizes, particularly those in high-stress industries, organizations with remote teams, and HR departments seeking to improve employee well-being and productivity
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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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Marlin
Optimized firmware for RepRap 3D printers based on Arduino platform
Marlin is a popular open source firmware for the RepRap family of 3D printers. It is straightforward, reliable, extensible and adaptable, which is why it is used by many respected commercial 3D printer vendors as well as hobbyists. It runs on inexpensive 8-bit Atmel AVR micro-controllers, with added support for 32-bit and ARM-based boards. Marlin builds can be small enough for use on a headless printer with only modest hardware, and features can be enabled as-needed. -
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CatBoost
High-performance library for gradient boosting on decision trees
CatBoost is a fast, high-performance open source library for gradient boosting on decision trees. It is a machine learning method with plenty of applications, including ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU... -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all... -
Give your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
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Quantum++
Modern C++ quantum computing library
Quantum++ is a modern C++ general-purpose quantum computing library, composed solely of template header files. Quantum++ is written in standard C++17 and has very low external dependencies, using only the Eigen 3 linear algebra header-only template library and, if available, the OpenMP multiprocessing library. Quantum++ is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken... -
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MultivariateStats.jl
A Julia package for multivariate statistics and data analysis
A Julia package for multivariate statistics and data analysis (e.g. dimensionality reduction). -
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LIBSVM.jl
LIBSVM bindings for Julia
LIBSVM bindings for Julia. This is a Julia interface for LIBSVM and for the linear SVM model provided by LIBLINEAR. Supports all LIBSVM models: classification C-SVC, nu-SVC, regression: epsilon-SVR, nu-SVR and distribution estimation: one-class SVM. Model objects are represented by Julia-type SVM which gives you easy access to model features and can be saved e.g. as JLD file. -
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle large-scale... -
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nut.js
Native UI testing / controlling with node
... to perform on-screen image search, the key component for visual testing or image-based automation! nut.js works on all major operating systems. Windows, macOS and Linux! An improved image matching plugin that supports Apple Silicon chips, works across all current and future node/Electron versions and provides multi-image matching. -
ConnectWise CPQ, formerly ConnectWise Sell, is a professional quote and proposal automation software for IT solution providers. ConnectWise CPQ offers a wide range of tools that enables IT solution providers to save time, quote more, and win big. Top features include professional quote or proposal templates, product catalog and sourcing, workflow automation, sales reporting, and integrations with best-in-breed solutions like Cisco, Dell, HP, and Salesforce.
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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ShinyItemAnalysis
Test and Item Analysis via Shiny
ShinyItemAnalysis is an R package including functions and interactive shiny application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters. Exploration of total and standard scores. Analysis of measurement error and reliability. Analysis of correlation structure and validity. Traditional item analysis. Item analysis with regression models. Item analysis with IRT models... -
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OceanBase
OceanBase is an enterprise distributed relational database
OceanBase Database is a native distributed relational database. It is developed entirely by Ant Group. OceanBase Database is built on a common server cluster. Based on the Paxos protocol and its distributed structure, OceanBase Database provides high availability and linear scalability. OceanBase Database is not dependent on specific hardware architectures. Single server failure recovers automatically. OceanBase Database supports cross-city disaster tolerance for multiple IDCs and zero data... -
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Argo Events
Event-driven Automation Framework for Kubernetes
Argo Events is an event-driven workflow automation framework for Kubernetes. It allows you to trigger 10 different actions (such as the creation of Kubernetes objects, invoking workflows or serverless workloads) on over 20 different events (such as webhook, S3 drop, cron schedule, messaging queues - e.g. Kafka, GCP PubSub, SNS, SQS). -
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DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based... -
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Gaius.jl
Divide and Conquer Linear Algebra
Gaius.jl is a multi-threaded BLAS-like library using a divide-and-conquer strategy to parallelism, and built on top of the fantastic LoopVectorization.jl. Gaius spawns threads using Julia's depth-first parallel task runtime and so Gaius's routines may be fearlessly nested inside multi-threaded Julia programs. Gaius is not stable or well-tested. Only use it if you're adventurous. -
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spaGO
Self-contained Machine Learning and Natural Language Processing lib
A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing. In other words, it has "zero dependencies", and we are committed to keeping it that way as much as possible. Spago uses a multi-module workspace... -
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Auto-PyTorch
Automatic architecture search and hyperparameter optimization
While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, another trend in AutoML is to focus on neural architecture search. To bring the best of these two worlds together, we developed Auto-PyTorch, which jointly and robustly optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Auto-PyTorch is mainly developed to support tabular data (classification, regression) and time series data... -
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NanoDet-Plus
Lightweight anchor-free object detection model
Super fast and high accuracy lightweight anchor-free object detection model. Real-time on mobile devices. NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss. In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training. We also introduce a light... -
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noUiSlider
JavaScript range slider with multi-touch and keyboard support
noUiSlider is a lightweight, ARIA-accessible JavaScript range slider with multi-touch and keyboard support. It is fully GPU animated: no reflows, so it is fast; even on older devices. It also fits wonderfully in responsive designs and has no dependencies. noUiSlider is a lightweight range slider with multi-touch support and a ton of features. It supports non-linear ranges, requires no external dependencies, has keyboard support, and it works great in responsive designs. Have you tried... -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can... -
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MultilayerGraphs.jl
Julia package for the creation and analysis of multilayer graphs
MultilayerGraphs.jl is a Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. A multilayer graph is a graph consisting of multiple standard subgraphs called layers which can be interconnected through bipartite graphs called interlayers composed of the vertex sets of two different layers and the edges between them. The vertices in each layer represent a single set of nodes, although not all nodes have to be represented in... -
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms... -
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Filament
Real-time physically based rendering engine for Android, iOS, and more
Filament is a real-time physically-based renderer written in C++. It is mobile-first, but also multi-platform. We are very conscientious about keeping Filament small, fast to load, and focused on rendering. For example, Filament does not compile materials at run time. Instead, we provide a command line tool (matc) that does this offline. Filament is a physically based rendering (PBR) engine for Android. The goal of Filament is to offer a set of tools and APIs for Android developers... -
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Phoronix Test Suite
Open-Source, Automated Benchmarking
The Phoronix Test Suite is the most comprehensive testing and benchmarking platform available that provides an extensible framework for which new tests can be easily added. The Phoronix Test Suite is designed to effectively carry out both benchmarks in a clean, reproducible, and easy-to-use manner. -
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AugmentedGaussianProcesses.jl
Gaussian Process package based on data augmentation, and sparsity
AugmentedGaussianProcesses.jl is a Julia package in development for Data Augmented Sparse Gaussian Processes. It contains a collection of models for different gaussian and non-gaussian likelihoods, which are transformed via data augmentation into conditionally conjugate likelihood allowing for extremely fast inference via block coordinate updates. There are also more options to use more traditional variational inference via quadrature or Monte Carlo integration.