Search Results for "em clustering algorithm" - Page 2
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Showing 62 open source projects for "em clustering algorithm"
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SKUDONET ADC, operates at the application layer, efficiently distributing network load and application load across multiple servers. This not only enhances the performance of your application but also ensures that your web servers can handle more traffic seamlessly.
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ChangeGear provides IT staff with the functions required to manage everything from ticketing to incident, change and asset management and more. ChangeGear includes a virtual agent, self-service portals and AI-based features to support analyst and end user productivity.
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Machine learning library that performs several clustering algorithms (k-means, incremental k-means, DBSCAN, incremental DBSCAN, mitosis, incremental mitosis, mean shift and SHC) and performs several semi-supervised machine learning approaches (self-learning and co-training). --------------------------------------------------------------------------- To run the library, just double click on the jar file. Also, you can use the following command line: Java -Xms1500m -jar "ML Library.jar...
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sdEM
Stochastic Discriminative Expectation Maximization (sdEM)
Stochastic discriminative EM (sdEM) is an online-EM-type algorithm for discriminative training of probabilistic generative models belonging to the natural exponential family. In this work, we introduce and justify this algorithm as a stochastic natural gradient descent method, i.e. a method which accounts for the information geometry in the parameter space of the statistical model. We show how this learning algorithm can be used to train probabilistic generative models by minimizing different... -
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ClusterMX
The ClusterMX program implements various clustering algorithms
The ClusterMX program implements various clustering algorithms including 1) K-Means clustering optimized by random walks; 2) Weighted K-Means (applying force filed to the multidimensional clustering space); 3) EM Clustering Algorithm; 4) Multi-Model Mean Shift Clustering with Random Sampling; 5) Unsupervised K-Wishart clustering. -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
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Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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SynergyTwo is ortholog clustering software for both prokaryotic and eukaryotic genomes. It requires Workflow (also available on sourceforge) to manage the computes. It is a reimplementation of the algorithm described in Wapinski et al Bioinformatics 2007.
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Unsupervised TXT classifier
Classify any two TXT documents, no training required - JAVA
This program is made to address two most common issues with the known classifying algorithms. First, over-training and second, shortage of data for a training of categories. Instead, each TXT file is a category on its own, rather than an assigned category. In a way, this is similar to clustering but not really a clustering algorithm since there is some training involved. The summarizer from Classifier4J has been adjusted to accept two inputs (lets call them A and B). Then, the summarizer gets... -
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VneCplus
虚拟网络映射的仿真器框架
VneCplus是一个虚拟网络映射的仿真器框架，其中实现了NC_DSBA算法，极大地提高了虚拟网络的映射性能。 NC_DSBA（Nodes Clustering and Dynamic Service Balance Awareness Algorithm）虚拟网络映射算法采用节点聚类的策略将虚拟网络请求分割为规模较小的子请求，分而治之，极大地降低了计算复杂度。采用PageRank计算每个节点的负载均衡能力和需求，从而使得虚拟网络请求的映射更趋于均衡，显著提高了虚拟网络映射的收益开销比和承载能力。 -
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QuasiRecomb
Probabilistic inference of viral Quasispecies
... parameters by analysing next generation sequencing data. We offer an implementation of the EM algorithm to find maximum a posteriori estimates of the model parameters and a method to estimate the distribution of viral strains in the quasispecies. The model is validated on simulated data, showing the advantage of explicitly taking the recombination process into account, and tested by applying to reads obtained from experimental HIV samples. -
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qure
software for viral quasispecies reconstruction from next-gen seq. data
QuRe is a program for viral quasispecies reconstruction, specifically developed to analyze long read (>100 bp) NGS data. The software performs alignments of sequence fragments against a reference genome, finds an optimal division of the genome into sliding windows based on coverage and diversity and attempts to reconstruct all the individual sequences of the viral quasispecies--along with their prevalence--using a heuristic algorithm, which matches multinomial distributions of distinct viral... -
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Enhanced Stable Election Protocol- SEP-E
An enhanced stable election protocol for wireless sensor network
While wireless sensor networks are increasingly equipped to handle more complex functions, in-network processing may require these battery powered sensors to judiciously use their constrained energy to prolong the effective network life time especially in a heterogeneous settings. Clustered techniques have since been employed to optimize energy consumption in this energy constrained wireless sensor networks. We propose an Enhanced-SEP clustering algorithm in a three-tier node scenario... -
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GSP program are based on Bayesian framework with an EM algorithm to predict genome size iteratively, which is elegant in mathematics. The model first develop under the no sequencing error model, then extend to the sequencing errors containing model.
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NeuralGas
Self-organized learning
A collection of algorithms based on the topology preserving Neural Gas algorithm for density estimation/quantization/clustering/self-organized learning. I moved this project to GitHub: https://github.com/sergioroa/neuralgas -
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EToS (Efficient Technology of Spike sorting; Extracellular recording To Spike trains) is an open-source system for spike sorting. EToS contains the programs of spike detection, feature extraction and clustering.
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EGA
A novel and effictive GA algorithm to solve optimization problem
Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments... -
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K-link
Read clustering algorithm which identifies and removes chimeric reads
This project was developed for ESTs. However, there is no reason it cannot be extended for use on amplicon sequences from 454. It is used in conjunction with WCDest clustering software. -
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PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
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Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
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This little software is the realization of EM algorithm in the application of tossiing the coin, which is described in the paper of Michael Collins in 1997.
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BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
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Fluster is a clustering algorithm for the Google Maps API v3. It manages all your markers on the map and summarizes them to "clustered markers" if there is not enough space around them. Acts like MarkerClusterer for v2.
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Java package to study a clustering model described in the paper \"Novel Clustering Algorithm Based Upon Games on Evolving Network\" by Q. Li, Z. Chen, Y. He and J-P. Jiang (in arxiv: http://arxiv.org/pdf/0812.5064v1), generalizations and similar issues.
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