Search Results for "clustering algorithm matlab" - Page 3
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Showing 162 open source projects for "clustering algorithm matlab"
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The purpose of this program is to provide the user with a convenient algorithm for automatic Independent Component (IC) selection with respect to the contributions of the ICs to a certain event-related brain potential (ERP). www.jan-wessel.de
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All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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TESTIMAGES
Testing images for scientific purposes
... patterns). Please cite the following papers when using any image in this archive: * ASUNI N, GIACHETTI A, "TESTIMAGES: A Large Data Archive For Display and Algorithm Testing", Journal of Graphics Tools, Volume 17, Issue 4, 2015, pages 113-125, DOI:10.1080/2165347X.2015.1024298 * ASUNI N, GIACHETTI A, "TESTIMAGES: a large-scale archive for testing visual devices and basic image processing algorithms", STAG - Smart Tools & Apps for Graphics Conference, 2014. -
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Density-ratio based clustering
Discovering clusters with varying densities
This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying... -
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This package includes a collection of MATLAB files which are designed to: 1. Given a calibration scan of the image of a point emitter with an engineered point spread function (PSF), 2. Perform a phase retrieval algorithm based on maximum likelihood estimation (MLE) of a phase aberration term which is added to the theoretical pupil function of the imaging system. 3. Use the phase-retrieved pupil function to perform single-emitter localization. Accompanying publication available here...
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QSdpR
Viral Quasispecies Reconstruction software based on QSdpR algorithm
This is a viral quasispecies reconstruction software for quasispecies assembly problem on mRNA viruses, which is based on a correlation clustering approach and uses semidefinite optimization framework. The software accepts a reference genome, a NGS read set aligned to this reference and set of SNP locations in the form of a vcf file and outputs an optimal set of reconstructed species genomes which describes the underlying viral population. -
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BISD
Batch incremental SNN-DBSCAN clustering algorithm
Incremental data mining algorithms process frequent up- dates to dynamic datasets efficiently by avoiding redundant computa- tion. Existing incremental extension to shared nearest neighbor density based clustering (SNND) algorithm cannot handle deletions to dataset and handles insertions only one point at a time. We present an incremen- tal algorithm to overcome both these bottlenecks by efficiently identify- ing affected parts of clusters while processing updates to dataset in batch... -
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CCKDM
Concern Mining
This is a tool for concern mining which uses a KDM model as input and the output is the same model with annotated concerns. It uses a Concern Library and a modified String Clustering K-means algorithm with Levenshtein metric to cluster the strings. -
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... of the Riemannian Hessian (if a Newton method is used) in Matlab or C++. The package optimizes the function given a set of user-specified parameters, e.g., the domain manifold, algorithm, stopping criterion.
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swe2d
Matlab 2D Shallow Water Solver
This is a set of matlab codes to solve the depth-averaged shallow water equations following the method of Casulli (1990) in which the free-surface is solved with the theta method and momentum advection is computed with the Eulerian-Lagrangian method (ELM). The free-surface equation is computed with the conjugate-gradient algorithm. Casulli, V. (1990) Semi-implicit finite difference methods for the two-dimensional shallow water equations, J. Comp. Phys., 86 (1), 56-74. -
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RDA Toolbox
MATLAB tool for analysis of Raman spectra.
Provides principal component analysis, discriminant analysis, peak analysis, and clustering tools powered by MATLAB in an easy-to-use interface for the interpretation of Raman spectroscopy data. -
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classify-20-NG-with-4-ML-Algo
Problem involves classifying 20000 messages into different 20 classes
.... Each of these algorithms has its peculiar data format; the specific format and how to reconstruct the entire dataset are illustrated in other sections below. Out of all the methods, SVM using the Libsvm [1] produced the most accurate and optimized result for its classification accuracy for the 20 classes. All the algorithm implementation was written Matlab. Download the code and Report here. -
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Object detection is usually a software-based monitoring algorithm that will signal, for example in the surveillance camera to begin capturing the event when it detects motion. In object tracking, the object is located and the moving object is followed. One of the fundamental steps in many computer based vision systems for object tracking and motion detection is real-time segmentation of moving regions in the image sequences. Segmentation is done in order to detect the object accurately...
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GI-ICA
Matlab implementation of GI-ICA and PEGI
This is a matlab implementation of the GI-ICA algorithm for ICA in the presence of an additive Gaussian noise. The algorithm is discussed in the paper "Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis" by James Voss, Luis Rademacher, and Mikhail Belkin. -
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Java Library for Machine Learning
A pure Java library for machine learning
JML is a machine learning library in Java, it is a pure Java package, and thus is cross-platform. The goal of JML is to make machine learning methods very easy to use and speed up code conversion from MATLAB to Java. Please be noted that JML has been replaced by LAML. -
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This site contains four packages of Mass and mass-based density estimation. 1. The first package is about the basic mass estimation (including one-dimensional mass estimation and Half-Space Tree based multi-dimensional mass estimation). This packages contains the necessary codes to run on MATLAB. 2. The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian...
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BiRW
Bi-random Walks for Phenome-Genome Association Prediction
The availability of ontologies and systematic documentations of phenotypes and their genetic associations has enabled large-scale network-based global analyses of the association between the complete collection of phenotypes (phenome) and genes. BiRW is a package designed for analysis and prediction of the phenome-genome associations. BiRW package contains a program for analysis of circular bigraphs (CBGs) and the bi-random walk (BiRW) algorithm to capture the CBG patterns in the networks... -
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JAABA
The Janelia Automated Animal Behavior Annotator
... detectors that can then be used to automatically classify the behaviors of animals in large data sets with high throughput. JAABA combines an intuitive graphical user interface, a fast and powerful machine learning algorithm, and visualizations of the classifier into an interactive, usable system for creating automatic behavior detectors. Documentation is available at: http://jaaba.sourceforge.net/ -
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Constrained Ellipse Fitting
MATLAB Code for Constrained Ellipse Fitting with Center on a Line
The provided Matlab code allows for fitting an ellipse to given data points with the additional prior knowledge that the center of the ellipse is located on a given line. The usage of this constraint in a new global convergent one-dimensional search problem ("Tunneling") improves the fitting accuracy compared to other ellipse fitting methods. You can find more details on the theoretical background of the presented algorithm here: http://doi.org/10.1007/s10851-015-0584-x If you use the code... -
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ObjectDetector
Car Detection,Face Detectiom,Object Detection
Machine learning: This project is used for training new object like Car,Motor Cycle and so on and we use this model(xml file) for detecting in images.In this project we use viola jones algorithm. -
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mAPV
modified Asymmetric Pseudo-Voigt Model
A new peak detection algorithm for MALDI mass spectrometry data based on a modified Asymmetric Pseudo-Voigt model -
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cusAPV
customized Asymmetric Pseudo-Voigt Model
A new peak detection algorithm for MALDI mass spectrometry data based on a customized Asymmetric Pseudo-Voigt model -
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Fuzzy clustering variation looks for a good subset of attributes in order to improve the classification accuracy of supervised learning techniques in classification problems with a huge number of attributes involved. It first creates a ranking of attributes based on the Variation value, then divide into two groups, last using Verification method to select the best group.Simon Fong, Justin Liang, YanZhuang, "Improving Classification Accuracy Using Fuzzy Clustering Coefficients of Variations...
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Unsupervised Random Forest
On-line Unsupervised Random Forest
This tool uses Random Forest and PAM to cluster observations and to calculate the dissimilarity between observations. It supports on-line prediction of new observations (no need to retrain); and supports datasets that contain both continuous (e.g. CPU load) and categorical (e.g. VM instance type) features. In particular, we use an unsupervised formulation of the Random Forest algorithm to calculate similarities and provide them as input to a clustering algorithm. For the sake of efficiency...
