Search Results for "clustering algorithm matlab" - Page 2
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Showing 162 open source projects for "clustering algorithm matlab"
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yafu
Automated integer factorization
Check yafu on github for the latest code. YAFU (with assistance from other free software) uses the most powerful modern algorithms (and implementations of them) to factor input integers in a completely automated way. The automation within YAFU is state-of-the-art, combining factorization algorithms in an intelligent and adaptive methodology that minimizes the time to find the factors of arbitrary input integers. Most algorithm implementations are multi-threaded, allowing YAFU to fully... -
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AmPEP and AxPEP
Sequence-based Antimicrobial Peptide Prediction by Random Forest
Antimicrobial peptides (AMPs) are promising candidates in the fight against multidrug-resistant pathogens due to its broad range of activities and low toxicity. However, identification of AMPs through wet-lab experiment is still expensive and time consuming. AmPEP is an accurate computational method for AMP prediction using the random forest algorithm. The prediction model is based on the distribution patterns of amino acid properties along the sequence. Our optimal model, AmPEP with 1:3 data... -
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This Matlab code is used for demonstration of the effect of CDF-TS as a preprocessing method to transform data. Written by Ye Zhu, Deakin University, April 2021, version 1.0. This software is under GNU General Public License version 3.0 (GPLv3) This code is a demo of method described by the following publication: Zhu, Y., Ting, K.M., Carman, M. and Angelova, M., 2021, April. CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities. Pattern...
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VOP post-processing
Post-processing algorithms for SAR compression
Here we introduce to algorithms for post-processing of VOP sets. Algorithm 1 reduces the Overestimation for a given set of VOPs. Especially useful to reduce the overestimation in VOP sets calculated with the compression algorithms by Lee et al. and Orzada et al. Algorithm 2 tests a given set of VOPs for redundancy. It can be used to reduce the number of VOPs in a dataset produced by Eichfelder and Gebhardt's algorithm. Especially useful when you have a vendor provided VOP set only. -
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Maxwell's-equations-derived-optimization
This project provide an open-source matlab code for MEDO.
... bar is treated as the region to be optimized, which is of the same shape with the objective function. According to the numerical tests, MEDO is proved to an effective optimization algorithm for both unimodal and multimodal functions. This version is created with MATLAB R2017a. -
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PyArmadillo
linear algebra library for Python
PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma -
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Isolation Similarity
aNNE similarity based on Isolation Kernel
Demo of using aNNE similarity for DBSCAN. Written by Xiaoyu Qin, Monash University, March 2019, version 1.0 This software is under GNU General Public License version 3.0 (GPLv3) This code is a demo of method described by the following publication: Qin, X., Ting, K.M., Zhu, Y. and Lee, V.C., 2019, July. Nearest-neighbour-induced isolation similarity and its impact on density-based clustering. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 4755-4762... -
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Relative Overestimation VOP
VOP compression for MRI with overestimation control
**** This work is outdated! For better compression and speed use these: ***** https://sourceforge.net/projects/enhanced-sar-compression/ Virtual Observation Points SAR compression. Contains multiple Algorithms: Compression according to Eichfelder et al. and Lee et al. The Lee algorithm is enhanced by including overestimation control to reduce maximum relative overestimation. All algorithms are implemented in Matlab and were optimized for enhanced speed. Needs Matlab R2016b at least... -
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A2RMS Algorithm
Implementation of the A2RMS Algorithm in Matlab
Implementation of the A2RMS Algorithm for univariate densities defined for real values. -
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LIPRAS, Line-Profile Analysis Software
Peak fitting GUI for diffraction data
LIPRAS v466 LIPRAS [LEEP-ruhs], short for Line-Profile Analysis Software, is a graphical user interface for least-squares fitting of Bragg peaks in powder diffraction data. For any region of the inputted data, user can choose which profile functions to apply to the fit, constrain profile functions, and view the resulting fit in terms of the profile functions chosen. If you use LIPRAS for your research, please cite it: Giovanni Esteves, Klarissa Ramos, Chris M. Fancher, and Jacob L.... -
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weka-MTreeClusterer
Flat clustering algorithm based on MTrees implemented for weka.
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DSeg software
A MATLAB program to segment filamentous bacteria and hyphae structures
The analysis of microscopy image has been the basis to our current understanding of the cellular growth and morphogenesis. The quantitative evaluation of morphological changes in the biological processes is therefore important to characterize cell structures. Here we present an image analysis tool DSeg to overcome the difficulties in finding complicated elongated cell shapes by using time-lapse data and cell morphological constraints. A fast binary level-set based algorithm is implemented... -
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Clustering by Shared Subspaces
Grouping Points by Shared Subspaces for Effective Subspace Clustering
These functions implement a subspace clustering algorithm, proposed by Ye Zhu, Kai Ming Ting, and Mark J. Carman: "Grouping Points by Shared Subspaces for Effective Subspace Clustering", Published in Pattern Recognition Journal at https://doi.org/10.1016/j.patcog.2018.05.027 -
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XBioSiP
RTL & Behavioral Models (Approx.) of Pan-Tompkins Application Stages
The "XBioSiP" library contains the RTL (VHDL) and behavioral (MATLAB) models of the approximate adders and multipliers used for designing approximate versions of the bio-signal processing Pan-Tompkins algorithm, including all of its application stages. This work was published in DAC 2019. In case of usage please refer to: B. S. Prabakaran, S. Rehman, M. Shafique, “XBioSiP: A Methodology for Approximate Bio-Signal Processing at the Edge”, IEEE/ACM 56th Design Automation Conference (DAC... -
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TBStudio
A quantum technical software to find Tight-Binding model of structures
TBStudio is a powerful quantum technical software package to construct Tight-Binding (TB) model for nano-scale materials. Starting from the simplified linear combination of atomic orbitals method in combination with first-principles calculations (such as OpenMX or Vasp packages), one can construct a TB model in the two-centre approximation. Using Slater and Koster approach we calculate the TB Hamiltonian of the system and use a nonlinear fitting algorithm to find the best entries for both... -
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Invariant curve calculations in Matlab
Calculating stable & unstable curves for 2 dimensional maps in matlab.
This is an implementation that follows closely the algorithm for calculating stable curves, described by J. P. England, B. Krauskopf, H. M. Osinga in the paper "Computing One-Dimensional Stable Manifolds and Stable Sets of Planar Maps without the Inverse" published in SIAM J. APPLIED DYNAMICAL SYSTEMS 3.2 (2004), 161-190. The package also contains an implementation for calculating the unstable curves which is based on the paper "Growing 1D and Quasi-2D Unstable Manifolds of Maps" by Bernd... -
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De_Lux
Deconvolution of luminescence cross-talk in microplate reader data
An algorithm to deconvolve the luminescence cross-talk in high-throughput gene expression profiling to recover the true luminescence activity of a microplate. -
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Distance Scaling
A Distance Scaling Method to Improve Density-Based Clustering
These functions implement a distance scaling method, proposed by Ye Zhu, Kai Ming Ting, and Maia Angelova, "A Distance Scaling Method to Improve Density-Based Clustering", in PAKDD2018 proceedings: https://doi.org/10.1007/978-3-319-93040-4_31. -
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Point Symmetry Clustering
Point Symmetry Clustering Approach Using Differential Evolution
Implementation of Point Symmetry-based Automatic Clustering Approach Using Differential Evolution Using bug fixed KD tree nearest neighbor search from https://github.com/CristianDallos/kmeansclustering. (It is also modified to search for multiple nearest points instead only for one.) Used those academic works for algorithm implementation: http://cs.cug.edu.cn/teacherweb/gwy/Publication/ISICA-09.pdf http://www.isical.ac.in/~sanghami/ieeetkde_cameraready.pdf http... -
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NNC
Nuclear Norm Clustering
We present Nuclear Norm Clustering (NNC), an algorithm that can be used in different fields as a promising alternative to the k-means clustering method, and that is less sensitive to outliers. The NNC algorithm requires users to provide a data matrix M and a desired number of cluster K. We employed simulate annealing techniques to choose an optimal L that minimizes NN(L). To evaluate the advantages of our newly developed algorithm, we compared the performance of both 16 public datasets and 2... -
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spark-msna
Algorithm on Spark for aligning multiple similar DNA/RNA sequences
The algorithm uses suffix tree for identifying common substrings and uses a modified Needleman-Wunsch algorithm for pairwise alignments. In order to improve the efficiency of pairwise alignments, an unsupervised learning based on clustering technique is used to create a knowledge base to guide them. -
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popt4jlib
Parallel Optimization Library for Java
popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known... -
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DGRLVQ
Dynamic Generalized Relevance Learning Vector Quantization
Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different... -
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UmUTracker
A MATLAB program for 2D particle tracking or 3D DHM based tracking.
We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing long video sequences acquired by either light microscopy or digital holography microscopy (DHM). Our program finds the 2D particle center position using an isosceles triangle transform and the axial position by a fast implementation of Rayleigh-Sommerfeld numerical reconstruction algorithm using a one dimensional radial intensity profile. *Updates v1.1: 2017/11/21- Bug... -
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A Generic Platform for Iris Recognition
A framework that allows iris recognition algorithms to be evaluated
This MATLAB based framework allows iris recognition algorithms from all four stages of the recognition process (segmentation, normalisation, encoding and matching) to be automatically evaluated and interchanged with other algorithms performing the same function. The algorithm for each stage can be selected from a list of available algorithms, with selection available for subfunctions as well. The selected algorithms can then be tested either manually against individual iris images...
