Search Results for "multiple regression"
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Showing 14 open source projects for "multiple regression"
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Agentless
An agentless approach to automatically solve software development
...When solving a problem, the system first performs localization to determine which files, functions, or code segments are most likely responsible for the issue. It then generates multiple candidate patches for the identified locations using language model reasoning and diff-style edits. In the final stage, the framework validates potential patches by running regression tests and additional reproduction tests to confirm whether the fix resolves the original error. Based on these results, the system ranks the candidate patches and selects the most reliable solution to submit. -
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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... -
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sktime
A unified framework for machine learning with time series
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation, and forecasting. It comes with time series algorithms and scikit-learn compatible tools to build, tune and validate time series models. Our objective is to enhance the interoperability and usability of the time series analysis ecosystem in its entirety. sktime provides a unified interface for distinct but related time series learning tasks. ... -
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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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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
...Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. Head over to our documentation to find out more about installation, creation of datasets and a full list of implemented methods and available datasets. -
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PostgresML
The GPU-powered AI application database
...Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. ... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
...It aims to strike a balance between theoretical explanation and practical coding by demonstrating algorithms both from scratch and using established libraries. The content is organized into multiple sections covering topics such as clustering, regression, dimensionality reduction, recommender systems, and model evaluation. -
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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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Physical Symbolic Optimization (Φ-SO)
Physical Symbolic Optimization
Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms. -
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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Zero to Mastery Deep Learning TensorFlow
All course materials for the Zero to Mastery Deep Learning with TF
This project is a comprehensive, code-first deep learning curriculum built around TensorFlow and Keras, designed to guide learners from foundational concepts to practical model deployment through hands-on experimentation. It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application. The material covers core machine learning workflows including... -
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Alink
Alink is the Machine Learning algorithm platform based on Flink
Alink is Alibaba’s scalable machine learning algorithm platform built on Apache Flink, designed for batch and stream data processing. It provides a wide variety of ready-to-use ML algorithms for tasks like classification, regression, clustering, recommendation, and more. Written in Java and Scala, Alink is suitable for enterprise-grade big data applications where performance and scalability are crucial. It supports model training, evaluation, and deployment in real-time environments and... -
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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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FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
...Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a semi-supervised anomaly detection strategy based on logistic regression. Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl. ... -
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Multi Expression Programming is a genetic programming method that encodes multiple solutions. It aims to solve difficult problems like classification or symbolic regression.
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