Search Results for "clustering algorithm matlab"
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Showing 183 open source projects for "clustering algorithm matlab"
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Clustering.jl
A Julia package for data clustering
Methods for data clustering and evaluation of clustering quality. -
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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms... -
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Math_Model is a repository collecting resources, code, and algorithm templates for mathematical modeling and competition (e.g. Chinese modeling contests, US undergraduate modeling competitions). It includes LaTeX templates for writing solutions, records of past contest problems and winning solutions, algorithm implementations in MATLAB / M scripts for optimization, intelligent algorithms, numerical methods, and model frameworks. In effect, it is a curated library of modeling code, papers...
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HDBSCAN
A high performance implementation of HDBSCAN clustering
HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection. In practice this means that HDBSCAN returns a good clustering straight away with little or no parameter tuning -- and the primary parameter, minimum cluster size... -
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MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
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Gait Tracking With x-IMU
Foot tracking algorithm demonstrated in Seb Madgwick's 3D Tracking
This repository provides the source code for a foot-tracking algorithm using an inertial measurement unit (IMU) attached to the foot, as demonstrated in Seb Madgwick’s “3D Tracking with IMU” video (March 2011). The method performs dead reckoning to integrate foot motion and corrects for drift at each foot strike (when the foot touches the ground) to reset error accumulation. The algorithm was part of gait analysis research, estimating foot trajectories in 3D over time. The repo is marked... -
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DeepSqueak
DeepSqueak Using Machine Vision to Accelerate Bioacoustics Research
Using Machine Vision to Accelerate Bioacoustics Research. -
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hctsa
Highly comparative time-series analysis
hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix. -
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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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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... -
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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... -
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TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
TIGRE is an open-source toolbox for fast and accurate 3D tomographic reconstruction for any geometry. Its focus is on iterative algorithms for improved image quality that have all been optimized to run on GPUs (including multi-GPUs) for improved speed. It combines the higher-level abstraction of MATLAB or Python with the performance of CUDA at a lower level in order to make it both fast and easy to use. TIGRE is free to download and distribute: use it, modify it, add to it, and share it. Our... -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
The Grey Wolf Optimizer for Path Planning is a MATLAB-based implementation of the Grey Wolf Optimizer (GWO) algorithm designed for UAV path and trajectory planning. It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during... -
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The Operator Splitting QP Solver
The Operator Splitting QP Solver
OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust. -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net... -
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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LRSLibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction
LRSLibrary is a MATLAB library offering a broad collection of low-rank plus sparse decomposition algorithms, primarily aimed at background/foreground modeling from videos (background subtraction) and related computer vision tasks. The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. The algorithms can also be adapted to other computer vision or machine learning problems beyond video. Large algorithm collection: > 100... -
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High-performance package for SemiDefinite Programs The software SDPA (SemiDefinite Programming Algorithm) is one of the most efficient and stable software packages for solving SDPs based on the primal-dual interior-point method.
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GRAMPC
A gradient-based augmented Lagrangian framework for embedded NMPC
GRAMPC is a nonlinear MPC framework that is suitable for dynamical systems with sampling times in the (sub)millisecond range and that allows for an efficient implementation on embedded hardware. The algorithm is based on an augmented Lagrangian formulation with a tailored gradient method for the inner minimization problem. GRAMPC is implemented in plain C with an additional interface to C++ and MATLAB/Simulink. The basic structure and usage of GRAMPC are described in the documentation... -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache... -
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syre
Synchronous Reluctance (machines) - evolution
SyR-e is a Matlab/Octave package developed to design, evaluate and optimize synchronous reluctance and permanent magnet machines. To perform Finite Element Analysis (FEA) SyR-e is linked to FEMM software, and the simulation process (model creation, pre-processing, post-processing) is automatic and completely controlled from SyR-e code. For the design section, SyR-e embeds automatic procedures based on design equations, minimal FEA simulations or multi-objective optimization algorithm joined... -
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Enhanced SAR Compression
VOP Algorithm with improved speed and compression
This work is described in: Orzada S, Fielder TM, Quick HH, Ladd ME, "A local SAR compression algorithm with improved compression, speed and flexibility", https://doi.org/10.1002/mrm.28739. This new algorithm is an iterative expansion of the exisisting local SAR compression algorithm for MRI proposed by Lee et al. ( https://doi.org/10.1002/mrm.23140) The number of VOPs is approximately halved with the new algorithm, while at the same time the compression time is reduced with speed-up... -
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iElectrodes
intracranial electrodes localization toolbox
iElectrodes is a free and open-source Matlab® toolbox to obtain intracranial electrode coordinates from MRI and CT images. Precise and reliable localization can be achieved fast and in a semiautomatic way with minimal user intervention. The toolbox works with ECoG (subdural grids and strips) and SEEG (depth) electrodes. The new GridFit algorithm can precisely localize high-density electrodes (up to 3mm). Brain parcellations (atlas) and surfaces can be imported to aid 2D and 3D visualization... -
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AngClust
AngClust: Angle-based feature clustering for time series
Citation: Aimin Li, Siqi Xiong, Junhuai Li, Saurav Mallik, Yajun Liu, Rong Fei, Hongfang Zhou, Guangming Liu. AngClust: Angle Feature-Based Clustering for Short Time Series Gene Expression Profiles. January 2022. IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM. DOI: 10.1109/TCBB.2022.3192306 Full text: https://ieeexplore.ieee.org/document/9833353/ https://pubmed.ncbi.nlm.nih.gov/35853049/ Highlights * We proposed a novel clustering algorithm based...
